A Simulation Platform for Combined Rail/Road...

Research ArticleA Simulation Platform for Combined RailRoad Transport inMultiyards Intermodal Terminals

Xuchao Chen 1 Shiwei He 1 Tingting Li 2 and Yubin Li 1

1School of Traffic and Transportation Beijing Jiaotong University Beijing 100044 China2School of Urban Planning and Design Shenzhen Graduate School Peking University Shenzhen 518055 China

Correspondence should be addressed to Shiwei He shwhebjtueducn

Received 28 September 2017 Revised 4 January 2018 Accepted 24 January 2018 Published 28 February 2018

Academic Editor Francesco Corman

Copyright copy 2018 Xuchao Chen et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

With the rapid development of multiyards railway intermodal terminal (MYRIT) construction in China performance evaluationhas become an important issue for terminal design and management departments Due to the complexity of the multiyardsterminal and the associated rail network the train moving process and related terminal operations have become more complicatedcompared with the traditional intermodal container terminal However in general simulation platforms the train moving processis simplified and train route scheduling rules are not considered in existing simulation models In order to provide an accurateand comprehensive quantitative evaluation tool for MYRIT a simulation platform based on the Timed Petri Net model has beendeveloped which can offer decision support for terminal design and management departments In this platform a yards andfacilities layout module has been created to give simulation users access to designing the railway network on this platform Anda train route dispatching simulation method has been integrated to provide an accurate simulation of the train moving processBased on a real case of Qianchang railway intermodal terminal that is located in Fujian Province China the platform is thoroughlyvalidated against historical data And the test scenarios show that train routes arrangement and handling equipment configurationboth have a significant influence on overall terminal performance which need to be carefully considered during terminal designand management

1 Introduction

In the past several years the Chinese logistics industryhas undergone a rapid development Along with the trendstoward the growing demands quantitatively and qualitativelyon the freight transportation system [1] a large-scale inter-modal terminal construction plan has been implemented byChina Railway Corporation According to the official docu-ment 33 1st-class 175 2nd-class and 300 3rd-class modernrailway intermodal terminals will be built from 2015 to 2017Different from the intermodal container terminals that havebeen widely constructed in Europe or America in the pastdecades the intermodal terminal in China usually containsmultiple cargo yards which can be called amultiyards railwayintermodal terminal (MYRIT) MYRIT is a kind of compre-hensive intermodal terminal which comprises distinguishedtypes of cargo yards in order to offer multimodal transportservices to different types of cargoes A typical MYRIT is

shown in Figure 1 which contains a bulk cargo (eg coal andore) yard a container yard a special cargo yard and others

In MYRIT different cargo yards provide services todifferent kinds of cargoes and contain independent facilities(railway tracks storage area handling equipment etc)resulting in a very complex process of terminal design whichinvolves a huge number of decisions [2] For a better terminaldesign one of the effective methods is simulation which canprovide performance evaluation of terminal design schemesbased on a simulation model In fact intermodal terminalscan be regarded as a kind of discrete event dynamic system(DEDS) of which the states only get changed at discretepoints in time as a result of stochastic events [3]

Due to the complexity of the MYRIT and the associ-ated railway network the train moving process simulationbecomes an important issue for overall terminal evalua-tion With various cargo yards the internal railway net-work involves more tracks switches and signals and the

HindawiJournal of Advanced TransportationVolume 2018 Article ID 5812939 19 pageshttpsdoiorg10115520185812939

2 Journal of Advanced Transportation

Figure 1 Typical layout of multiyards railway intermodal terminal

interaction of train routes becomes more complicated whichhas a significant influence on the train moving processHowever in existing simulation platforms there has beena lack of simulation methods which can provide a detailedsimulation of the train moving process The train movingprocess has been simplified in most general simulationmodels which will lead to an inaccuracy in the terminalevaluation

In order to provide an accurate and comprehensivesimulation ofMYRIT a simulation platform is developed andpresented in this paper which can be used as an analysisand predictive tool for terminal design and managementdepartments In this platform a yards and facilities layoutmodule has been invented which can be used for inputtingand editing the railway network of a multiyards terminaland a train route dispatching simulation method (TRDSM)has been created to provide an accurate simulation of thetrain moving process considering basic dispatching rulesThe architecture and the simulation model of the platformare elaborated in this paper and it should be noted thatthis platform is dedicated to railroad intermodal terminalsand terminals which involve waterway transportation likecontainer ports are not applicable to this system

The remaining part of this paper is organized as followsIn the following section a literature review of intermodalterminal optimization and management based on simulationtechniques is provided Then in Section 3 an overview ofoperations of MYRIT and the framework of this simulationplatform are presented In Section 4 the simulation modelsbased onTimed Petri Net (TPN) and key simulationmethodsintegrated in the platform are expounded In Section 5 thefunction introduction of the simulation platform thatwe havedeveloped is given In Section 6 validation and some testscenarios of the simulation platform are detailed Finally asummary of this study follows and possible extensions onintermodal terminal simulation are identified

2 Literature Review

Simulation techniques have been used successfully in termi-nal planning design and optimization problems and thereare many literatures in this field Rizzoli et al [4] built asimulation model of the flow of intermodal terminal units(ITUs) among and within inland intermodal terminals using

MODSIMIII as a development tool During the simulationvarious statistics are gathered to assess the performance ofthe terminal equipment Another simulation tool dedicatedto model a single terminal was introduced by Benna andGronalt [5] Terminal layout arrival patterns of trains andtrucks and container settings were specified as part of theinput data A general overview of the macro and micromodel was provided by Ballis and Golias [6] They tested themicro model for 17 different terminal layouts with varyingnumbers of tracks and cranes as well as lifting technologiesMarinov and Viegas [7] provided a yard simulationmodelingmethodology for analyzing and evaluating flat-shunted yardoperations using SIMUL8 A comparative evaluation tool forrailroad freight transport terminals has been developed byBallis and Golias [8] which consists of three models (anexpert system a simulation model and a cost calculationmodel) Fugihara et al [9] provided a way of simulation tech-nology which can generate several benefits in the distributioncenter projects

This paper focuses on the simulation of railroad inter-modal terminals however some literatures with regard toseaport terminal simulation can also be used as referencesHartmann [10] provided an approach for generating sce-narios of seaport terminals which can support solving opti-mization problems in container terminal logistics Vis [11]compared the use of manned straddle carriers with that ofautomated stacking cranes The total travel time required tohandle all container moves was applied as a performancemeasure to determine the yard layout for the seaport termi-nal A computer simulation model with on-screen animationgraphics which can simulate the operations of a containerterminal equipped with straddle carriers was introduced byBallis and Abacoumkin [12] Based on this model differentconfigurations (changes in yard layout equipment numberand productivity truck arrival pattern and service discipline)of the simulated system can be evaluated Shabayek andYeung [13] developed a simulation model to simulate KwaiChung container terminals in Hong Kong using Witnesssoftware The layout of the port and the incoming andoutgoing routes for container vessels were considered in themodel which can provide a prediction of terminal operationswith a high order of accuracy

PetriNet iswidely used for the description of the structureand dynamics of DES [14] For more details of the Petri Net

Journal of Advanced Transportation 3

theory and modeling refer to Peterson [15] and David andAlla [16] A great number of successful Petri Net modelshave been designed for terminal simulation and optimizationthroughout the world Some of the most relevant ones areexpanded in the following paragraphs Dotoli et al [17]addressed the issue of modeling and managing IntermodalTransportation Systems (ITS) at the operational level Thesystem is highly complex with various types of conveyancesalongside scheduling aspects A Timed Petri Net frameworkwas built to model the ITS which contains the tollboothhighways truck railway port and ship subsystems A similarexploration has been performed by Maione and Ottomanelli[18] A container terminal simulation model was proposedwithin the theoretical framework of Petri Nets which allowstaking into account the different aspects of the consideredsystem Lee et al [19] presented the development and appli-cation of simulation models for air cargo terminal operationsusing Timed Color Petri Net (TCPN) The TCPN is able tosimulate the operations of various types of material handlingequipment and is validated based on actual cargo retrievalschedules records A high-level Petri Net model whichcontains timed predicatetransition net has been providedby Hsu et al [20] This model aims at solving the threeessential operational problems (berth allocation problemquay crane assignment problem and quay crane schedulingproblem) of container terminals simultaneously which canresult in good overall system performance Cavone et al [21]proposed a procedure for planning and managing resourcesin intermodal terminals which integrates Timed Petri Netsand Data Envelopment Analysis Silva et al [22] describedthe modeling of a container terminal using Petri Net withpredicates which allowed the evaluation of different configu-rations and combinations of transport equipment providinga very complete port system simulation A general modelingframework based on Timed Petri Net was constructed byDotoli et al [23] which allowed simulating and evaluatingthe performance of key elements within the intermodaltransportation chain In the Petri Net model places representresources and capacities or conditions transitions modelinputs flows and activities into the terminal and tokensrepresent intermodal transport units

Previous findings show that the simulation method hasbeen very effective and was widely used in the field ofterminal optimization and management These manuscriptsprovide valuable supports for our work the simulationframework control methods of the terminal entities andPetri Net models of terminal activities are used as referencesin our simulation platform However there has been a lackof simulation methods considering multiple cargo yardsand most papers focus on container terminal simulationWith only one type of cargo the structure of the containerterminal and the associated railway network is relativelysimple compared with MYRIT The simulation model of thetrain moving process is simplified to a single discrete eventin great majority of existing studies and detailed train routescheduling rules are not considered However due to thecomplexity of the rail network in MYRIT the interactionof train movements can have a significant influence on thetrain moving process and terminal performance Therefore

a detailed simulation method of the train moving processconsidering train route dispatching rules has been consideredas an important element in this platform

3 Framework Design

MYRIT is a kind of multimodal freight hub where differenttypes of cargoes are delivered and picked up by trains ortrucks Cargoes arrive at terminal by trainstrucks and areunloaded in corresponding yards by cargo-handling appli-ances (gantry cranes forklifts reach stackers etc) Certaingoods are picked up by trainstrucks directly while somegoods need to be processed and stored within the terminalfor a period of time before they are picked up Variousfacilities and equipment are needed to finish these taskssuch as railway tracks platforms handlingmachineries truckparking lots and repertories which constitute a large-scaleintricate logistics system In this section the main operationsof MYRIT which are considered in the TPN model areintroduced and the framework of the simulation platform isdescribed as well

31 Overview of MYRIT Operations The main operationsin MYRIT can be divided into three components namelythe train operations the truck operations and the cargo-handling operations

311 Train Operations There are four prime steps of trainoperations When an inbound train arrives at the terminalit enters the receiving-departure yard (or arriving yard) firstand then undergoes an arrival inspection (cargo informationcheck safety inspection etc) conducted by a surveyor Afterthat according to the type of goods carried by the train theoccupancy states of tracks in the corresponding cargo yardare checked If there are idle side tracks within the yardthe inbound train will move into the target yard under thecommand of the train dispatching office The cargo load-ingunloading operations are implemented inside the cargoyard bymeans of certain cargo-handling appliancesThe typeand mechanical model of appliances depend on the physicalnature of the cargoes In case the loadingunloading machineis busy the train will stay on the side track and wait to beserved When the cargo loadingunloading task is finishedthe outbound train will move back to the receiving-departureyard (or departure yard) and a departure inspection will becarried out At last the outbound train leaves the terminalat the time required by the timetable It should be notedthat sometimes the outbound train can leave the terminalfrom the cargo yard directly without entering the departureyardThe typical trajectories of train operations are shown inFigure 2

312 Truck Operations Trucks arrive at MYRIT to delivercargoes to outbound trains or to pick up cargoes frominbound trains When a truck arrives at the entrance gateof the terminal it joins a first-in first-out (FIFO) queueand waits for arrival inspection which is implemented bythe gate system The arrival inspection includes collecting


Special cargo yard

Receiving-departure yard

Container yard

Bulk cargo yard

①

(a) Inbound train arrives at the arriving yard

Special cargo yard


Container yard

Bulk cargo yard

②

(b) Inbound train moves to the cargo yard

Special cargo yard


Container yard

Bulk cargo yard

③

(c) Outbound train moves to the departure yard

Special cargo yard


Container yard

Bulk cargo yard

④

(d) Outbound train departs from the terminal

Figure 2 Trajectories of train operations

information of trucks and goods through a high-resolutioncamera weighing arrival trucks and providing guidanceinformation for truck drivers Several factors can influencethe work efficiency of arrival inspection such as the numberof gates the number of entrance channels the location ofgates and the degree of automation of gate informationmanagement system

After the arrival inspection the arrival truckmoves to thecorresponding cargo yard according to the guidance informa-tion from the gate system When the truck enters the cargoyard in the majority of cases it will join a FIFO queue in theloadingunloading area If there are available cargo-handlingmachineries the truck loadingunloading procedure beginsWhen the truck has been loaded or unloaded it will move tothe exit gate of the terminal Similar to the entry process thedeparture truck needs a departure inspection at the exit gate

In addition to the trucks mentioned above there isanother type of trucks which are called the shuttle trucksShuttle truckswork inside the terminal and are used for trans-porting goods between different cargo yards The number ofshuttle trucks is much lower than the number of externaltrucks which will leave the terminal when the loading andunloading tasks are completed Shuttle trucks can be regardedas a kind of equipment resources of MYRIT The sketch mapof the truck operations within MYRIT is shown in Figure 3

313 Cargo-Handling Operations There aremultiple types ofhandling machineries inMYRIT such as gantry cranes frontlifters reach stackers and forklifts Each kind of machineryhas different mechanical properties and serves differenttypes of cargoes in diverse cargo yards The cargo-handlingoperations can be divided into two types according to thedelivery direction of the goods the train-truck operationwhich represents the handling operation of goods deliveredby trains and picked up by trucks and the truck-trainoperation which represents the handling operation of goodsdelivered by trucks and picked up by trains In this sectionthe train-truck cargo-handling operation is introduced as arepresentative

When the cargo which is delivered by inbound trainsis about to be unloaded within the cargo yard one of thefollowing three circumstances is given

(i) If the corresponding truck which is used for pickingup the cargo has arrived at the cargo yard the cargo will beunloaded directly from the inbound train to the truck In thissituation only one loadingunloading operation is required

(ii) If the corresponding truck cannot catch up with thedeadline (the timewhen the inbound train has been unloadedandmust leave) the cargowill be unloaded to the storage areainside the cargo yard and stored there After that when thecorresponding truck arrives at the cargo yard the cargo willbe loaded from the storage area to the truck In this case twoloadingunloading operations are required

(iii) If the cargo needs special storage condition (egrefrigerated container) or the cargo needs to be processedinside MYRIT (eg express parcels need to be sorted inthe sorting workshop of MYRIT before they are picked upby shippers) it will be unloaded to the shuttle truck anddelivered to the corresponding area (as shown in Figure 3)

The process of truck-train operation is basically contraryto the process of the train-truck operation and also can bedivided into three cases Due to the limitation of the spaceand avoidance of repetition the details of this procedure arenot discussed here

32 Framework of Simulation Platform Based on the opera-tions overview of MYRIT the framework of this simulationplatform is shown in Figure 4The framework has four layersnamely the Petri Net layer the simulator layer the layoutlayer and the user layer which are elaborated as follows

(i) Petri Net layer the Petri Net layer is the basis ofthe simulation platform which composes three TPNmodels that is the train operation model the truckoperation model and the cargo-handling model

(ii) Simulator layer the simulator layer contains the coresimulation modules and key methods integrated inthis platform including the train generation method


Entrance gate

Exit gate

Yard craneStorage area


Cargo yard

Cargo yard

Parkingarea

Truck unloadedTruck loadedShuttle truck

Storage area forspecial cargo

Figure 3 Scheme of truck operations in multiyards railway intermodal terminal

Layoutlayer

Parameter settingUserlayer

Simulation operation control

Simulation resultspresentation

User interfaces

Yards amp facilities module

Position parameters Order parameters Type parameters

Simulatorlayer

Simulation module

Train arrival-departureoperation

Truck arrival-departure operation

Cargo-handling operation

Methods and techniques

Train generation methodTrain route dispatching

simulation method Truck generation method

Petri Netlayer

Petri Net model of train operations

Petri Net model of truck operations

Petri Net model of cargo-handling operations

Figure 4 Framework of simulation platform

the truck generation method and the train routedispatching simulation method

(iii) Layout layer the layout layer contains the yards andfacilities layout module which allows users to designor modify the yards and facilities (tracks switches

signal machines etc) locations by adjusting certainparameters Three types of parameters are designedas follows

(a) Position parameters which determine the rela-tive position relation (horizontal and vertical)


between certain cargo yard and the receiving-departure yard

(b) Order parameter which determines the relativeposition relation among different cargo yards

(c) Type parameter which determines the type ofcertain cargo yard According to the layout ofrail tracks cargo yards can be classified into 3types through-type cargo yard stub-end-typecargo yard and mixed-type cargo yard

(iv) User layer the user layer contains the operationcontrol module the simulation project database thesimulation results database and related interfacesSimulation users are able to access this layer to set upa simulation project control the simulation progressand obtain the simulation analysis results via user-friendly interfaces

4 Simulation Model

Petri Net is a widely used tool using graphic elements asa representation to describe the structure and dynamicsof DEDS such as computer systems and manufacturingsystems TPN is a bipartite diagraph described by the five-tuple as shown in the following formula

TPN = (119875 119879PrePost 119865) (1)

where 119875 represents the set of places with |119875| = 119898 119879 is the setof transitionswith |119879| = 119899 Pre is the preincidencematrixwithPre 119875 times 119879 rarr 119873119898times119899 Post is the postincidence matrix withPost 119875 times 119879 rarr 119873119898times119899 and the function 119865 119879 rarr 119877+ specifiesthe timing associated with each transition

A simulation model has been established based on TPNin this study There are three types of transitions used in thismodel immediate transition stochastic transition and deter-ministic timed transition Corresponding to the operations ofMYRIT the TPN model is segmented into three submodelswhich are the train arrival and departure model the truckarrival and departure model and the cargo-handling model

41 Train Arrival and Departure Model

411 Train Generation Method This platform provides twotypes of train generationmethodsThe first one is to generateinbound trains according to a fixed timetable input bysimulation users Each train arrival time is generated basedon a historical record of train arrival events This methodapplies to the terminals which have been put into use and isparticularly useful to perform trace-driven simulation

The second method is to generate inbound trains arrivalsaccording to a stochastic mathematical distribution which isspecified by simulation usersThis generationmethod appliesto the terminals that are still in the stage of design or construc-tion and it can be used to test alternative arrival patterns

412 Train Route Dispatching Simulation Method As intro-duced above TRDSM is created to simulate the train dis-patching operation which can provide an accurate simulation

R3

R2 R1

Figure 5 Diagram of train route samples

of the train moving process According to the relationshipbetween two different train routes train routes pairs can bedivided into two types conflicting train routes pair (CTRP)and parallel train routes pair (PTRP) Train routes in CTRPcontain some of the same equipment As shown in Figure 5train route 1198771 (the golden line) shares a section of track(marked by the red circle) with train route 1198772 (the blue line)whichmeans if train route1198771 is occupied by a train then trainroute 1198772 becomes unavailable as well because it is impossiblefor two trains to move on the same track simultaneously

Contrary to the CTRP there is no space conflict in PTRPTrain route 1198771 is independent of train route 1198773 (the greenline) whichmeans if one train occupies1198771 another train canoccupy 1198773 at the same time

Based on the analysis of different types of train routespairs the framework of the TRDSM is presented in Figure 6and the main steps are as follows

Step 1 (train route database presetting) There are varioustrain routes in MYRIT The train routes of different types oftrains and different train move events are diverse All trainroutes should be set by simulation users in advance accordingto the station operation regulations and all the preconfiguredtrain routes are stored in the database

Step 2 (generating trainmove request) Trainmove request isgenerated from the trains which have finished the precedingoperation and are ready to move to the next operatinglocation or the trains which have been added to the waitingqueue for available train route When a train move request isgenerated the corresponding train routewill be invoked fromthe train route database

Step 3 (examining the availability of train route) The avail-ability of train route is determined by the availabilities of thekey points (switches and signal machines) within it To bespecific only when all key points of the train route are notoccupied can this train route be available Otherwise thistrain route is unavailable and the corresponding train willjoin the FIFO queue

Step 4 (generating train move event) If the train route isavailable it will be occupied by the train and a train moveevent will be generated The occupancy states of the keypoints in this train route will be updated based on the real-time location of the moving train

Step 5 (examining the waiting queue) If all train moverequests have been executed the method stops Otherwiseanother train move request is generated according to theFIFO rules and the method returns to Step 2


Train route database presetting

Generating train move request

Examining the availabilityof train route

Generating train move eventUpdating the states of

key points

Train waiting queue

Stop

No

No

Yes

Yes

Selecting train route from database

Have all move requests been satisfied

Figure 6 Framework of train route dispatching simulation method

413 Description of Train Arrival and Departure Model TheTPNmodel of train arrival and departure process is presentedin Figure 7 Train generation is represented by a stochastictransition T1 For an inbound train (P1) when it is about toenter the arriving yard (or the receiving-departure yard) (T2)the availabilities of the destination track and the correspond-ing train route must be checked places P3 and P4 are addedto represent the available destination track and the availabletrain route respectively Similarly for each train movingevent (T4 T7 T8 and T9) the availabilities of tracks andtrain routes must be checked The availability inspection oftrain route is realized based on TRDSM which is representedby an immediate transition T10 To check the availabilities oftrain routes the real-time location information of the trainwhich is expressed by several places (P17 P19 P20 and P22)needs to be acquired Places P5 and P6 represent the emptyinbound train and the loaded inbound train respectivelyCorrespondingly P7 indicates the train which has beenloaded and P8 indicates the train which has been unloaded

For outbound trains two places (P9 and P10) are addedto represent trains with different departure modes Place P9indicates the trains which can leave the terminal directlywithout moving to the departure yard (or the receiving-departure yard) while place P10 indicates the trains whichneed to finish the departure inspection at the departureyard before leaving the terminal Transition T6 is added todistinguish different train departure modes

42 Truck Arrival and Departure Model

421 Truck Generation Method A truck generation methodis designed to generate stochastic arrivals of trucks accordingto certain mathematical distribution According to the studyby Rizzoli et al [4] the truck arrival pattern can be approxi-mately described by the negative exponential distribution

422 Description of Truck Arrival and Departure ModelWhen a truck is generated by the truck generation method(T11) it joins a FIFO queue at the entrance gate An arrivalinspection (T12) will begin if there is a free entrance channelwhich is represented by the place P38

Considering that the time cost of the truck movingprocess is not fixed the truck moving process inside theterminal (from the terminal gate to a certain cargo yard andvice versa) is represented by two stochastic transitions (T14and T17) And the time cost of truck moving is producedbased on stochastic distribution Place P37 indicates theavailable parking spaces within the cargo yard And T18 isa deterministic timed transition which represents the depar-ture inspection of outbound trucks The TPNmodel of truckarrival and departure process is also presented in Figure 7

43 Cargo-Handling Model Corresponding to the cargo-handling operations the cargo-handling model can also bedivided into two submodels the train-truck cargo-handling


Train-truckcargo-handling model

Train arrival and departure model

Truck-traincargo-handling model

Truck arrival and departure model

T1 T2 T3 T4 T5 T6 T7 T8 T9

T10

T11 T12 T13 T14 T15 T16 T17 T18 T19

T20 T21

T22

T23

T24 T25 T26

T27 T28 T29

T32

T30

T33

T34 T35

T36

T37

T38 T39 T40

T41 T42 T43 T44

T46

P1 P3 P4P2P5

P6

P7

P8

P9

P10

P11P12

P13P14

P15

P16 P17 P18 P19 P20 P21

P15

P23

P24

P25

P37

P26

P27 P28 P29P30P31

P32P33

P34 P35

P36P38

P39

P40

P41

P42 P43 P44

P46

P45

P47 P48 P49 P50 P51

P52

P54

P55

P56

P57

P58

P59 P60 P61

P62

P63

P64 P65 P66 P67 P68

P69

P71

T47

P72

P53

T31

P70

T45

Immediate transition

Stochastic transition

Deterministic timed transition

P22

Figure 7 TPN model of multiyards railway intermodal terminal

model and the truck-train cargo-handling model which areshown in Figure 7 In this section the train-truck model isintroduced as a representative

The cargo which needs processing operation in MYRIT(or needs to be stored in a special area) is represented by placeP47 This kind of cargo needs to be picked up by the shuttletrucks and carried to the corresponding area (T28) Threedeterministic timed transitions (T27 T29 and T31) are addedto represent the cargo unloading event from trains to shuttletrucks the cargo unloading event from shuttle trucks to themachining region (or storage area for special goods) andthe cargo loading event from machining region (or storagearea for special goods) to consigneersquos trucks respectivelyTheprocessing operation is represented by transition T30 PlaceP52 represents the resources for processing operation and P53represents the available shuttle trucks

Normal cargo which does not need to be machinedor stored in the special area is represented by place P40Place P41 represents the cargo as described in case (i) inSection 313 which can be picked up by trucks directly PlaceP42 represents the cargo which needs to be stored withinthe terminal temporarily The cargo unloading event and the

storage process are represented by transitions T24 and T25respectively Place P48 indicates the available storage space

Four transitions (T32 T33 T46 and T47) are added toconnect different submodels T32T46 indicates the event ofgenerating loaded outbound trucktrain when the loadingoperation has been finished and T47T33 represents theevent of generating empty outbound trucktrain when theunloading operation is completed

5 Multiyards Railway Intermodal TerminalSimulation Platform

Based on the TPN model a multiyards railway intermodalterminal simulation platform is developed using C asa development tool The MYRIT simulation platform canprovide realistic reproduction of the main logistic activitiesand entities flows (eg trains trucks and cargoes) whichoccur inside the terminal It can be used to evaluate theterminal design scheme andmanagement strategies based onthe quantitative analysis of simulation results and to providedecision support for terminal planning and design In thissection a brief introduction of this platform is presented


Figure 8 Interface of terminal layout planning

Figure 9 Interface of train route presetting

As mentioned above terminal layout has a significantimpact on the train operations and should be determinedfrom the very beginning of setting up a simulation projectIn this platform a graphical interface (as shown in Figure 8)for layout planning of MYRIT is provided where simulationusers can design or modify the terminal layout by setting theparameters as introduced in Section 32

Once the terminal layout has been identified the struc-ture of the internal railway network of MYRIT can be deter-mined Simulation users should preset train routes accordingto the station operation regulations via an interface of trainroute presetting as shown in Figure 9 The internal railwaynetwork of MYRIT is described by the lines which representthe rail tracks and the points with unique ID numbers whichrepresent the center points of the turnouts Each train routecan be represented by a sequential list of ID numbers asshown in Figure 9 (eg the red train route is representedby the numeral string ldquo44-45-1-2-3-12rdquo) The intersectionsamong various train routes may cause train congestion in therail yard and can lead to efficiency decline of train operations

A statistical analysis of the performance of storage areacan be provided by the platform As shown in Figure 10a sketch map of the operation in cargo yard during thesimulation is reported A train is being unloaded within the

cargo yard and a truck arrives to pick up cargoThe real-timevolume curve of the cargoes which are stored in the storagearea is displayed Based on the detailed records of the cargovolumes the utilization ratio of storage area in a certain cargoyard can be calculated as shown on the right side of Figure 10

In Figure 11 several indexes of the cargo volumes arereported The pie chart shows the proportion of the quantityof each type of goods to the total volume of goods duringthe simulation period And from the histogram the volumeof each type of goods delivered by trains and trucks and thevolume of each type of goods picked up by trains and truckscan be obtained A group of line charts show the relationshipsbetween the volumes of inbound cargo and outbound cargo

Based on the TRDSM this platform can provide elaboratereproduction of the trainmoving process within the terminaland major time information of the train moving processcan be accessed by users via the interface as shown inFigure 12 A detailed statistical analysis of train performancecan be obtained on the platform based on the simulationresults Several statistical charts about train operation timeare reported in Figure 13 Among them the first chart showsthe number of trains and the time consumption of trainsstaying at the cargo yard


Figure 10 Snapshot of the platform interface during simulation

Figure 11 Statistical analysis of cargo volumes based on the simulation results

The utilization ratio of handling equipment can also beanalyzed An example of the historical record of the craneutilization ratio in the container yard during the simulationperiod is shown in Figure 14 Utilization ratio is one of thekey indicators of handling equipment which reflects the busydegree of the equipment resources In general low utilizationratio may indicate that there is a problem of equipmentredundancy and high utilization ratio (in a reasonable range)means the handling equipment is fully used Therefore fromthe perspective of investment benefit high utilization ratiois more likely to be beneficial for the investors Howeverexorbitant high utilization ratio also means possibility ofhaving lengthy truck queue in the cargo yard Therefore thequeue length of trucks needs to be analyzed as well Thesample result of truck queue length in cargo yard is presentedin Figure 15

6 Validation and Test Scenarios ofSimulation Platform

Validation is extremely important in the validation phaseto ensure that the result of the simulation model is able toreproduce the reality under different conditions [24] In thissection a simulation case of Qianchang railway intermodal

terminal has been performed to verify the capacity of theplatform of reproducing the real terminal behavior And twotest scenarios are presented to investigate the impact of vari-ations of train route arrangement and handling equipmentconfiguration on terminal performance

61 Simulation Case Setup The simulation case is set upbased on the Qianchang railway intermodal terminal whichis located in Fujian Province China Qianchang railwayintermodal terminal provides transport services of varioustypes of cargoes including commercial vehicles electrome-chanical equipment steel products and cold chain goodsTheintermodal terminal covers an area of more than 2 squarekilometers which contains one receiving-departure yard andseven independent cargo yards These cargo yards consist ofa bulk cargo yard for steel products a bulk cargo yard forgrain crops a container yard a bulky cargo yard an expresscargo yard an automobile cargo yard for commercial vehiclesand a special cargo yard for cold chain cargoes The layout ofQianchang terminal edited by the yards and facility moduleof the simulation platform is shown in Figure 16

The initial data used in the validation is provided by theQianchang railway intermodal terminal based on a monthlystatistical report The dataset spans a 30-day period and


Figure 12 Time information of the train moving process

Dwell time in cargo yard

151 2 25 3 35 4 45 5 55 6 6505Dwell time (h)

020406080

Trai

ns

(a)

Average loadingunloading time in each yard

Bulk

carg

o ya

rd

Lugg

age e

xpre

ss y

ard

Con

tain

er y

ard

Bulk

y ca

rgo

yard

Expr

ess c

argo

yar

d

Auto

mob

ile y

ard

Spec

ial c

argo

yar

d

02468

10

Tim

e (h)

(b)

Con

tain

er y

ard

Bulk

carg

o ya

rd

Auto

mob

ile y

ard

Lugg

age e

xpre

ss y

ard

Bulk

y ca

rgo

yard

Spec

ial c

argo

yar

d

Expr

ess c

argo

yar

d

002040608

112

Tim

e (h)

Average waiting time in each yard

(c)Figure 13 Statistical analysis of train performance

Idle timeService time

12 24 36 48 60 72 84 96 108 1200Time (h)

0

20

40

60

80

100

Util

izat

ion

ratio

Figure 14 Crane utilization ratio in container yard

records detailed information on several key performanceindicators which include the cargo volumes average trainloadingunloading time average truck terminal dwell timeand utilization rate of handling machineries

Queue length of truck waiting in bulk cargo yard

10 20 30 40 50 60 70 80 90 100 110 1200Time (min)

01234

Que

ue le

ngth

Figure 15 Queue length of trucks in bulk cargo yard

62 Results and Analysis Considering the variability in thesimulation procedure the results used for validation aresummarized from a set of 500 simulations which providereliable simulation statistics of the activities within the inter-modal terminal The efficiency of the constructed simulationframework ensures that a single repetition costs about 47seconds on a 25GHz i5-3210M dual-core processor with


Automobile yard

Express cargo yard

Container yard


Bulk cargo yard (steel products) Bulk cargo yard(grain crops)

Special cargo yard

Bulky cargo yard

Figure 16 Yards layout of Qianchang railway intermodal terminal

Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l

Historical dataSimulation data

09

092

094

096

098

1

102

104

Figure 17 Normalized cargo volumes from historical and simula-tion datasets

4 GB of RAM To provide intuitive comparative analysisresults in the validation phase most simulated values arenormalizedwith respect to the values in the historical datasetwhich means the value of 1 corresponds to the actual value inthe real life system

In Figure 17 we present a bar plot of the normalized cargovolumes (the total volume and the respective volumes foreach type of cargo) of the historical data and the simulationdata which are in the 95 confidence interval The blackbars on histograms indicate the minimum and maximumof the simulation data Although the trains and trucks aregenerated according to the historical record the specificcapacity of each railway wagon and truck and all types ofdelays (the delays that are related to the lack of railway trackshandling equipment and warehouses) introduce variabilitiesin the quantity of cargo volume The differences between

the simulated and actual data are very limited The biggestdifference of simulated data in 95 confidence interval isbelow 2 which suggests good agreement with the historicaldataset

A similar study is performed in the case of utilization ratesof handling machineries as presented in Figure 18 where thebars also indicate the limits of the 95 confidence intervalThe utilization rates of machineries in seven cargo yards aremeasured and displayed in the histograms which vary widelyfrom yard to yard The utilization of handling equipmentin the express cargo yard almost reached 50 while theutilization rates in grain crops yard and special cargo yardare below 20 Returning to the analysis of the validationthe similarity of handling machineries utilization is againnoticeable As shown in Figure 18 the differences betweenthe simulated utilization rates and real utilization rates arebelow 2 and 95 of the simulation results lie within 5 ofthe expected value whichmeans the simulation platform canreproduce the activities of handling machineries accurately

Figures 19 and 20 display the normalized train load-ingunloading time accumulated by each train from thehistorical and simulation dataset in the same order Inspecific each loadingunloading time is normalized withrespect to the actual mean loadingunloading time whichis 2660 minutes As shown in Figure 19 most data pointsare scattered in the interval from 03 to 20 and have noapparent patterns However a noticeable feature is that somedata points are concentrated on the horizontal line with thevalue of 04 (as shown by the orange dotted line in Figure 19)and are relatively far from the rest of the points These datapoints correspond to the container trainswhich can be loadedor unloaded with higher stevedoring efficiency with thesupport of gantry cranes In fact the historical average load-ingunloading time of container trains is 1003minutes whichis only 376 of the overall mean loadingunloading time

These characteristics are all reflected in the simulatedresults as shown in Figure 20 To verify the similarities


Historical data Simulation data000

1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()

Express cargo yardGrain crops yardContainer yardSpecial cargo yard

Bulky cargo yardAutomobile yardIron products yard

Figure 18 Historical and simulated utilization ratio of handlingmachineries

Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25

Figure 19 Historical train loadingunloading time distribution

between the historical data and simulation data in the futurewe employ the two-sample Kolmogorov-Smirnov test toassess the quantitative differences between the distributionsThe progressive significance coefficient (119901 value) is 0553which is significantly higher than the typical mark of 005This verification indicates that the simulated train load-ingunloading time distribution is statistically not differentfrom the historical record and hence describes an accuraterepresentation

To verify the simulation accuracy of truck operationprocedures the total dwell time at the intermodal terminalis calculated as one of the key performance indicatorsConsidering the large quantity of trucks which are more than30000 it is difficult for the scatter plot to display the inherentlaw of the data intuitively Therefore histograms are usedto describe the distribution of the total truck dwell timewhich are shown in Figures 21 and 22 Similarly the dwelltime of each truck has been normalized with respect to thehistorical mean dwell time and the simulated distribution isdrawn based on the simulation results which are in the 95confidence interval

As shown in the histograms the simulated dwell timedistribution is very similar to the actual time distribution

Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25

Figure 20 Simulated train loadingunloading time distribution

Dwell time

05 1 15 2 25 30Normalized total dwell time

0

500

1000

1500

2000

2500

3000

Freq

uenc

y

Figure 21 Historical distribution of total terminal dwell time oftrucks

overall Both distributions have multipeaks and great major-ity of data points are clustered in the section from 50 to150of themeandwell time It is easy to explain this relativelystrong variation in the dwell time distribution In Qianchangintermodal terminal there are multiple types of trucks Dueto the differences in cargo characteristics the dwell time ofdifferent types of truck tends to have obvious differences Infact the historical mean dwell time of container trucks is23 less than the average dwell time of special cargo trucksIn Figure 22 the red continuous vertical line indicates thevalue of the historical mean dwell time and the green dottedline illustrates the average simulated dwell time within the95 confidence interval and the difference is negligible Thetwo distributions have been again compared in terms of thetwo-sample Kolmogorov-Smirnov test with 119901 value of 0484which is significantly larger than 005The test result indicatesthat the simulation platform reproduces the activities of thereal life system accurately

In order to further verify the effectiveness of the simu-lation data the mean error 119863(119876) which is proposed in theliterature [25] (defined in (2)) is introduced to quantify themean absolute percentage error In (2) 119876 is defined as aquantity of one indicator119876ℎ is introduced as notation for thehistorical value of this indicator and119876119904 is defined as the valueof the respective indicator obtained in the 119894th simulationFurthermore the percentage error between the simulated


Table 1 Simulation error coefficient results

Cargo type Error coefficients IndicatorsCargo volume Utilization rate Loadingunloading time Dwell time

Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347

Dwell timeHistorical mean timeAverage simulation time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y

Figure 22 Simulated distribution of total terminal dwell time oftrucks

data and the historical value is described by 119864(119876) which isdefined in (3)

119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)

A detailed error coefficient analysis of the four keyperformance indicators is summarized in Table 1 The meanerror 119863(119876) and the percentage error 119864(119876) of each type ofcargo are calculated based on the historical record and thesimulation data which are in the 95 confidence intervalThe mean errors of the cargo volumes are obviously smallwhich is consistent with the results in Figure 17 The errorcoefficients of truck dwell times are relatively higher whichcan be explained as follows Since there is no fixed timetablefor truck activities (which is different from trains) the trucks

are designed to mainly follow the principle of FIFO rule inthe simulation model which is mentioned in Section 42However in practice the queuing rule is more flexible andis easy to be artificially changed which obviously affects thedwell time of trucks As for trains the arrival and departuretime of trains are determined by the timetable which reducesthe variabilities in the simulation process to a certain extentThis deviation can be narrowed by introducing more flexiblequeuing rules into the simulation model in the future

In general the similarities between the simulation dataand the actual record are noticeable The biggest percentageerror is smaller than 4 and the percentage errors ofmost performance indicators are less than 2 Following thecomprehensive analysis of both qualitative and quantitativefeatures the simulated results have been proved to have goodagreements with the historical values which is able to verifythe validity of this simulation platform

63 Test Scenarios Having established the convincing per-formance of the model via several validation studies we nowaim to use the platform as a decision-support and predictivetool Some test scenarios of relevance for the activities inMYRIT have been formulated

In Section 631 we describe the impact of train routearrangement on train operation efficiency Two train routeschemes are analyzed based on simulation results Then inSection 632 we pursue to investigate the effects of handlingequipment configuration variation on loadingunloadingoperations Some suggestions on equipmentmanagement aregiven according to the simulation analysis

631 Train Route Arrangement Train moving procedure isone of the most important terminal activities within MYRITThis process has an instant impact on the train operations andcan influence all relevant workflows of the terminal Insidethe MYRIT each train must move in accordance with theprescribed train route Due to the complexity of the railway


Bulky cargo yardSpecial cargo yard

Grain yardDeparture lines

Receiving lines

Container yardSteel yard

Train route of entering cargo yard

Train route of leaving cargo yard

E1

L1

L2

(a) Scheme A

Grain yard

Special cargo yardBulky cargo yard

Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B

Figure 23 Two local train routesrsquo arrangement schemes of Qianchang railway terminal

Table 2 Performance indicators of the train moving process based on simulation tests

Train type Scheme A Scheme BMDTRY (min) MDTCY (min) MDTRY (min) MDTCY (min)

Bulky cargo 318 3238 337 3187Grain 317 2178 339 2126Container 319 4282 34 4225Steel 32 1208 331 1307Special cargo 1174 3924 1212 4225

line topology in MYRIT train route arrangement can havea significant influence on train moving efficiency and is animportant issue in the field of terminal management

The goals of train route arrangement include reducingroutes conflicts and improving trainmoving efficiency Basedon the simulation platform the performance of certain trainroute arrangement can be analyzed and different arrange-ment schemes can be compared and selected based on sim-ulation results In this section we construct a simulation testwhich contains two partial train route arrangement schemesof Qianchang railway intermodal terminalThe detailed trainroute schemes are shown in Figures 23(a) and 23(b)

The two train route schemes shown in Figure 23 showpartof the overall train route arrangement scheme of Qianchangterminal which mainly contain the train routes of enteringcargo yards and leaving cargo yards According to the direc-tion the train routes which are shown in these two schemescan be divided into three types the train routes of enteringbulky special and grain cargo yards which are named 1198641the train routes of leaving bulky special and grain cargoyards which are named 1198711 and the train routes of leavingcontainer and steel cargo yards which are named 1198712 Thedetailed arrangements of 1198641 routes in Scheme A and SchemeB are different while other train routes in the two schemes arethe same To investigate the influences of these two train routeschemes on the efficiency of the train moving proceduresimulation experiments are implementedWith the exceptionof the train routes variation all other parameters are designedin the same manner as in the validation study

Table 2 summarizes the results of the investigationTwo indicators are used to analyze the train operationefficiency which are the mean dwell time in receiving yard(MDTRY) and the mean dwell time in cargo yard (MDTCY)Each indicator is calculated based on the values from 500

597694 658

344 324

Bulky Grain Special Container Steel

Percentage of MDTRY increase in Scheme B compared to Scheme A

000

200

400

600

800

()

Figure 24 Differences of MDTRY between Scheme A and SchemeB

simulation repetitions which are in the 95 confidenceinterval Since the inspection time in receiving yard andthe loadingunloading rates in cargo yards are the samein the two simulation experiments the indicators of dwelltime can reflect the performances of train moving efficiencyFigures 24 and 25 present the visualizations of the findingsin Table 2 which show the value differences on indicatorsbetween Scheme A and Scheme B

We notice an obvious increase on MDTRYs when usingScheme B as shown in Figure 24 Compared with Scheme Athe MDTRYs of bulky grain and specially cargo trains havebeen extended by about 6 which indicates that the routes1198641 in Scheme B have more conflicts with other train routesThe train routes of entering cargo yard for container and steelcargo trains are the same in both Scheme A and Scheme BHowever the MDTRYs of container and steel cargo trainsin Scheme B are still about 3 larger than the MDTRYs in


minus158minus239 minus133

820 767

Percentage of MDTCY increase in Scheme B compared to Scheme A

minus400

minus200

000

200

400

600

800

1000

()

SteelContainerSpecialGrainBulky

Figure 25 Differences of MDTCY between Scheme A and SchemeB

Scheme A In terms of dwell time in cargo yard theMDTCYsof container and steel cargo trains in SchemeB have increasedsharply compared with the MDTCYs in Scheme A while theMDTCYs of bulky grain and special cargo trains have beenreduced This phenomenon indicates that in Scheme B theperformance of 1198711 train routes has been improved comparedto Scheme A however the conflicts between 1198712 and othertrain routes have become more serious

The reason of the simulation results needs to be analyzedThere are train routes conflicts in both SchemeA and SchemeB In Scheme A routes 1198641 mainly have conflicts with routes1198711 while in Scheme B routes 1198641 mainly have conflicts withroutes 1198712 However the number of trains which need tooccupy 1198711 and the number of trains that need to occupy 1198712are different In fact the total number of container and steelcargo trains is 52 larger than the total number of bulkygrain and special cargo trains which makes the conflictsbetween 1198641 and 1198712 much more serious than the conflictsbetween 1198641 and 1198711 Hence the MDTRY of bulky grainand special cargo trains and the MDTCY of container andsteel cargo trains are all increased when using Scheme BIn addition since the MDTCY of container and steel cargotrains increased these types of trains need to wait more foravailable side tracks in the receiving yard which leads to anincrease in the MDTRY of container and steel cargo trainsAlthough the MDTCY of bulky grain and special cargotrains decreased when using Scheme B the MDTCY of alltrains in Scheme B is still 39 larger than that of Scheme A

Therefore in general Scheme A has advantages overScheme B in train operation efficiency And in reality SchemeA is adopted by the dispatch department of QianchangterminalThe simulation tests show that the number of trainsis one of the key factors in train route dispatching It can beinferred that when the quantity of trains changes greatly trainroutes schemes need to be adjusted accordingly

632 Handling Equipment Configuration The second set ofinvestigations is constructed in order to study the impactof varying handling equipment configuration on perfor-mance indicators of loadingunloading operation Generallyincreasing the quantity of handling equipment can reduce theloadingunloading time and improve the operation efficiency

However the quantitative relationship between the perfor-mance indicators of loadingunloading operation and theequipment quantity needs to be analyzed which can providedecision-support information for the terminal managers

Considering the realistic quantity limitations of themachineries we are interested in what happens when thequantity of handling equipment is varied from 50 to 150of the current value in Qianchang terminal The incrementis set to 25 leading to a total of 5 studies each designedto collect statistics from 500 simulations The performanceindicators include themean laytime of train (MLT Train) themean laytime of truck (MLT Truck) the mean waiting timefor handling operation of train (MWT Train) and the meanwaiting time for handling operation of truck (MWT Truck)which are calculated from the 95 confidence interval of thesimulation results and are normalized with respect to thehistorical values The results are shown in Figure 26 wherewe present the lower upper and mean values of the relevantindicators obtained from the simulation tests

It can be observed that increasing the handling equipmentquantity can lead to a decrease in laytime and waiting timeof trains and trucks However the sensitivities of the fourindicators are different

As the machinery quantity increases the decreases ofMLT Train and MLT Truck are both almost linear whichis easily understood However the variation of MLT Trainis much bigger than the variation of MLT Truck Thisphenomenon is caused by the difference between the equip-ment usage pattern of trains and that of trucks In generalmost types of trains can be unloadedloaded by multiplehandling machineries at the same time Therefore with theincrease of handling equipment the loadingunloading ratesof trains rise simultaneously Nevertheless except for bulkcargo trucks and express cargo trucks many types of trucks(eg bulky cargo trucks container trucks and automobiletrucks) can only be served by one handling machine dueto the characteristics of goods Thus with the increaseof handling equipment quantity the growth of the overallloadingunloading rate of all types of trucks ismoremoderatecompared with trains And little variation of MLT Truck canbe observed with the increase of handling equipment

We notice a strong link between the MWT TrainMWT Truck and machinery quantity dynamics A 50decrease of handling equipment can cause almost 130increase of the waiting time of trains and almost 100increase of the waiting time of trucks Very large variation ofwaiting time indicates that reduction of availablemachineriescan significantly reduce the efficiency of loadingunloadingoperation Hence maintaining an efficient stevedoring ser-vicing is vital to the terminal system

As the handling equipment quantity increases boththe means and variations in MWT Train and MWT Truckdecrease obviously However the rates of decline graduallyslow down It can be inferred that even with more handlingmachineries the waiting time of trains and trucks in theterminal does not completely disappear In fact with another50 increase of handling equipment (200 of the currentvalue) only 8 decrease of MWT Train and 5 decreaseof MWT Truck can be obtained We can conclude that


075 100 125 150050

Relative quantity of handling equipment

040

060

080

100

120

140

160

180La

ytim

e of t

rain

s

Region of interestHistorical laytimeMaximum laytime

Mean laytimeMinimum laytime

(a) Laytime of trains



050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150


(b) Laytime of trucks

Region of interestMaximum wait timeMean wait timeMinimum wait timeHistorical wait time

000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns

075 100 125 150050Relative quantity of handling equipment

(c) Wait time for loadingunloading of trains

Region of interestHistorical wait timeMaximum wait time

Mean wait timeMinimum wait time

050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050


(d) Wait time for loadingunloading of trucks

Figure 26 Impact of handling equipment configuration variation on loadingunloading operation efficiency

in Qianchang intermodal terminal increasing the handlingequipment to more than 150 of the current value wouldonly lead to negligible improvements of loadingunloadingefficiency With this conclusion future investment and man-agement of handling equipment can be considered in areasonable and efficient manner

7 Conclusions and Future Work

A simulation platform for providing a quantitative evaluationofMYRIThas been presentedThe simulationmodel includesthree sub-TPN models which correspond to the three majoroperations of MYRIT In this platform a yards and facilitieslayout module has been created where users can flexiblydesign or modify the terminal layout and a TRDSM hasbeen designed to provide an accurate simulation of thetrain moving process Based on a comprehensive simulationanalysis of Qianchang railway intermodal terminal the sim-ulation platform has been proved to be able to reproduce the

activities of the real life system accurately In addition usefulsuggestions for terminal design and management can beobtained based on simulation tests of train route arrangementand handling equipment configuration

Compared with existing simulationmodels this platformhas advantage in providing a detailed simulation of trainmoving process considering train routes dispatching rulesThe results in the case study indicate that integrating thecontrol method of train route dispatching can significantlyimprove the simulation accuracy of MYRIT In generalthis simulation platform can be used as an evaluation andanalysis tool for terminal planning and design departmentsMoreover with the support of the yards and facilities moduleand the TRDSM it can also be used as a managementdecision-support tool for dispatching managers

Some limitations of the current simulation platformand the simplification procedure within the TPN modelneed to be analyzed which can be considered as suggestedimprovements to the platform in future research


Firstly in the TPN model the truck moving process hasbeen simplified as one discrete event and the connectionsbetween adjacent trucks and truck congestion circumstancesare not considered which will lead to inaccurate simulationresults when the truck flow rate of the terminal is hugeThis could be improved by integrating a car-following modelinto the simulation platform Secondly the basic queuingrule adopted by the platform is FIFO policy Nevertheless insome circumstances the EDD (earliest due date) or WSPT(weighted shortest processing time first) rules can be usedto reduce the delay time and sometimes queuing rules areartificially determined In most situations this is a suitableassumption since most of the terminal activities are requiredto follow the principle of FIFO rule However a study ofmixed queue policy might provide possible improvementFinally an optimizationmechanism is not taken into accountin the framework which can be improved For examplenumerous optimization methods have been proposed in thefield of train route scheduling [26ndash28] Some of the methodscan be integrated into the platform to perform a simulation-based train route optimization for terminal managers Andin terms of determining equipment configuration or terminallayout developing an integral approach considering multipleinput scenarios can be a valuable future research directionwhich can assist the terminal designers in a good terminaldesign

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This research is jointly supported financially by the NationalNatural Science Foundation of China (no 61374202)National Key RampD Program of China (2016YFE0201700) theResearch Project of China Railway Corporation (2017X004-D 2017X004-E) and the Fundamental Research Funds forthe Central Universities (2017YJS098)

References

[1] H SMahmassani K Zhang J Dong C-C Lu V C Arcot andE Miller-Hooks ldquoDynamic network simulation-assignmentplatform for multiproduct intermodal freight transportationanalysisrdquo Transportation Research Record no 2032 pp 9ndash162007

[2] B C Kulick and J T Sawyer ldquoUse of simulation modelingfor intermodal capacity assessmentrdquo in Proceedings of the 2000Winter Simulation Proceedings pp 1164ndash1167 December 2000

[3] S Hou ldquoDistribution center logistics optimization based onsimulationrdquo Research Journal of Applied Sciences Engineering ampTechnology vol 5 no 21 pp 5107ndash5111 2013

[4] A E Rizzoli N Fornara and L M Gambardella ldquoA simulationtool for combined railroad transport in intermodal terminalsrdquoMathematics and Computers in Simulation vol 59 no 1ndash3 pp57ndash71 2002

[5] T Benna and M Gronalt ldquoGeneric Simulation for rail-roadcontainer Terminalsrdquo in Proceedings of the Winter SimulationConference pp 2656ndash2660 Miami Fla USA December 2008

[6] A Ballis and J Golias ldquoTowards the improvement of acombined transport chain performancerdquo European Journal ofOperational Research vol 152 no 2 pp 420ndash436 2004

[7] M Marinov and J Viegas ldquoA simulation modelling method-ology for evaluating flat-shunted yard operationsrdquo SimulationModelling Practice andTheory vol 17 no 6 pp 1106ndash1129 2009

[8] A Ballis and J Golias ldquoComparative evaluation of existing andinnovative rail-road freight transport terminalsrdquoTransportationResearch Part A Policy and Practice vol 36 no 7 pp 593ndash6112002

[9] M K Fugihara A Audenhove and N T Karassawa ldquoRan-domless as a critical point Simulation fitting better planning ofdistribution centersrdquo in Proceedings of the Conference onWinterSimulation pp 2371-2371 2007

[10] S Hartmann ldquoGenerating scenarios for simulation and opti-mization of container terminal logisticsrdquo OR Spectrum vol 26no 2 pp 171ndash192 2004

[11] I F A Vis ldquoSurvey of research in the design and controlof automated guided vehicle systemsrdquo European Journal ofOperational Research vol 170 no 3 pp 677ndash709 2006

[12] A Ballis and C Abacoumkin ldquoA container terminal simulationmodel with animation capabilitiesrdquo Journal of Advanced Trans-portation vol 30 no 1 pp 37ndash57 1996

[13] A A Shabayek and W W Yeung ldquoA simulation model forthe Kwai Chung container terminals in Hong Kongrdquo EuropeanJournal of Operational Research vol 140 no 1 pp 1ndash11 2002

[14] J Montoya Francisco and R K Boel ldquoIntroduction to DiscreteEvent Systemsrdquo IEEE Transactions on Automatic Control vol46 no 2 pp 353-354 2002

[15] J L Peterson ldquoPetri net theory and the modeling of systemsrdquoComputer Journal vol 25 no 1 1981

[16] R David and H Alla Discrete Continuous and Hybrid PetriNets Springer-Verlag Berlin Heidelberg Germany 2005

[17] M Dotoli M P Fanti A M Mangini G Stecco and WUkovich ldquoThe impact of ICT on intermodal transportation sys-tems a modelling approach by Petri netsrdquo Control EngineeringPractice vol 18 no 8 pp 893ndash903 2010

[18] G Maione and M Ottomanelli ldquoA Petri net model for simu-lation of container terminal operationsrdquo Advanced OR and AIMethods in Transportation pp 373ndash378 2005

[19] C Lee H C Huang B Liu and Z Xu ldquoDevelopment oftimed Colour Petri net simulationmodels for air cargo terminaloperationsrdquo Computers amp Industrial Engineering vol 51 no 1pp 102ndash110 2006

[20] H-P Hsu C-N Wang C-C Chou Y Lee and Y-F WenldquoModeling and solving the three seaside operational problemsusing an object-oriented and timed predicatetransition netrdquoApplied Sciences (Switzerland) vol 7 no 3 article no 218 2017

[21] G Cavone M Dotoli N Epicoco and C Seatzu ldquoIntermodalterminal planning by Petri Nets and Data Envelopment Analy-sisrdquo Control Engineering Practice vol 69 pp 9ndash22 2017

[22] C A Silva C Guedes Soares and J P Signoret ldquoIntermodalterminal cargo handling simulation using Petri nets with pred-icatesrdquo Proceedings of the Institution of Mechanical EngineersPart M Journal of Engineering for the Maritime Environmentvol 229 no 4 pp 323ndash339 2015

[23] M Dotoli N Epicoco M Falagario and G Cavone ldquoA TimedPetri Nets Model for Performance Evaluation of IntermodalFreight Transport Terminalsrdquo IEEETransactions onAutomationScience and Engineering vol 13 no 2 pp 842ndash857 2016


[24] M Bielli A Boulmakoul and M Rida ldquoObject orientedmodel for container terminal distributed simulationrdquo EuropeanJournal of Operational Research vol 175 no 3 pp 1731ndash17512006

[25] R Cimpeanu M T Devine and C OrsquoBrien ldquoA simulationmodel for the management and expansion of extended portterminal operationsrdquo Transportation Research Part E Logisticsand Transportation Review vol 98 pp 105ndash131 2017

[26] P Pellegrini G Marliere J Rodriguez and G MarliereldquoOptimal train routing and scheduling for managing trafficperturbations in complex junctionsrdquo Transportation ResearchPart B Methodological vol 59 pp 58ndash80 2014

[27] M Sama P Pellegrini A DrsquoAriano J Rodriguez and DPacciarelli ldquoAnt colony optimization for the real-time trainrouting selection problemrdquo Transportation Research Part BMethodological vol 85 pp 89ndash108 2016

[28] M Sama A DrsquoAriano F Corman and D Pacciarelli ldquoAvariable neighbourhood search for fast train scheduling androuting during disturbed railway traffic situationsrdquo Computersamp Operations Research vol 78 pp 480ndash499 2017

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Figure 1 Typical layout of multiyards railway intermodal terminal

interaction of train routes becomes more complicated whichhas a significant influence on the train moving processHowever in existing simulation platforms there has beena lack of simulation methods which can provide a detailedsimulation of the train moving process The train movingprocess has been simplified in most general simulationmodels which will lead to an inaccuracy in the terminalevaluation

In order to provide an accurate and comprehensivesimulation ofMYRIT a simulation platform is developed andpresented in this paper which can be used as an analysisand predictive tool for terminal design and managementdepartments In this platform a yards and facilities layoutmodule has been invented which can be used for inputtingand editing the railway network of a multiyards terminaland a train route dispatching simulation method (TRDSM)has been created to provide an accurate simulation of thetrain moving process considering basic dispatching rulesThe architecture and the simulation model of the platformare elaborated in this paper and it should be noted thatthis platform is dedicated to railroad intermodal terminalsand terminals which involve waterway transportation likecontainer ports are not applicable to this system

The remaining part of this paper is organized as followsIn the following section a literature review of intermodalterminal optimization and management based on simulationtechniques is provided Then in Section 3 an overview ofoperations of MYRIT and the framework of this simulationplatform are presented In Section 4 the simulation modelsbased onTimed Petri Net (TPN) and key simulationmethodsintegrated in the platform are expounded In Section 5 thefunction introduction of the simulation platform thatwe havedeveloped is given In Section 6 validation and some testscenarios of the simulation platform are detailed Finally asummary of this study follows and possible extensions onintermodal terminal simulation are identified

2 Literature Review

Simulation techniques have been used successfully in termi-nal planning design and optimization problems and thereare many literatures in this field Rizzoli et al [4] built asimulation model of the flow of intermodal terminal units(ITUs) among and within inland intermodal terminals using

MODSIMIII as a development tool During the simulationvarious statistics are gathered to assess the performance ofthe terminal equipment Another simulation tool dedicatedto model a single terminal was introduced by Benna andGronalt [5] Terminal layout arrival patterns of trains andtrucks and container settings were specified as part of theinput data A general overview of the macro and micromodel was provided by Ballis and Golias [6] They tested themicro model for 17 different terminal layouts with varyingnumbers of tracks and cranes as well as lifting technologiesMarinov and Viegas [7] provided a yard simulationmodelingmethodology for analyzing and evaluating flat-shunted yardoperations using SIMUL8 A comparative evaluation tool forrailroad freight transport terminals has been developed byBallis and Golias [8] which consists of three models (anexpert system a simulation model and a cost calculationmodel) Fugihara et al [9] provided a way of simulation tech-nology which can generate several benefits in the distributioncenter projects

This paper focuses on the simulation of railroad inter-modal terminals however some literatures with regard toseaport terminal simulation can also be used as referencesHartmann [10] provided an approach for generating sce-narios of seaport terminals which can support solving opti-mization problems in container terminal logistics Vis [11]compared the use of manned straddle carriers with that ofautomated stacking cranes The total travel time required tohandle all container moves was applied as a performancemeasure to determine the yard layout for the seaport termi-nal A computer simulation model with on-screen animationgraphics which can simulate the operations of a containerterminal equipped with straddle carriers was introduced byBallis and Abacoumkin [12] Based on this model differentconfigurations (changes in yard layout equipment numberand productivity truck arrival pattern and service discipline)of the simulated system can be evaluated Shabayek andYeung [13] developed a simulation model to simulate KwaiChung container terminals in Hong Kong using Witnesssoftware The layout of the port and the incoming andoutgoing routes for container vessels were considered in themodel which can provide a prediction of terminal operationswith a high order of accuracy

PetriNet iswidely used for the description of the structureand dynamics of DES [14] For more details of the Petri Net





3 Framework Design






Special cargo yard


Container yard

Bulk cargo yard

①


Special cargo yard


Container yard

Bulk cargo yard

②


Special cargo yard


Container yard

Bulk cargo yard

③


Special cargo yard


Container yard

Bulk cargo yard

④
















Entrance gate

Exit gate



Cargo yard

Cargo yard

Parkingarea




Layoutlayer




User interfaces



Simulatorlayer

Simulation module







Petri Netlayer














4 Simulation Model


TPN = (119875 119879PrePost 119865) (1)







R3

R2 R1















key points

Train waiting queue

Stop

No

No

Yes

Yes
















T1 T2 T3 T4 T5 T6 T7 T8 T9

T10

T11 T12 T13 T14 T15 T16 T17 T18 T19

T20 T21

T22

T23

T24 T25 T26

T27 T28 T29

T32

T30

T33

T34 T35

T36

T37

T38 T39 T40

T41 T42 T43 T44

T46

P1 P3 P4P2P5

P6

P7

P8

P9

P10

P11P12

P13P14

P15

P16 P17 P18 P19 P20 P21

P15

P23

P24

P25

P37

P26

P27 P28 P29P30P31

P32P33

P34 P35

P36P38

P39

P40

P41

P42 P43 P44

P46

P45

P47 P48 P49 P50 P51

P52

P54

P55

P56

P57

P58

P59 P60 P61

P62

P63

P64 P65 P66 P67 P68

P69

P71

T47

P72

P53

T31

P70

T45




P22






























151 2 25 3 35 4 45 5 55 6 6505Dwell time (h)

020406080

Trai

ns

(a)


Bulk

carg

o ya

rd

Lugg

age e

xpre

ss y

ard

Con

tain

er y

ard

Bulk

y ca

rgo

yard

Expr

ess c

argo

yar

d

Auto

mob

ile y

ard

Spec

ial c

argo

yar

d

02468

10

Tim

e (h)

(b)

Con

tain

er y

ard

Bulk

carg

o ya

rd

Auto

mob

ile y

ard

Lugg

age e

xpre

ss y

ard

Bulk

y ca

rgo

yard

Spec

ial c

argo

yar

d

Expr

ess c

argo

yar

d

002040608

112

Tim

e (h)




12 24 36 48 60 72 84 96 108 1200Time (h)

0

20

40

60

80

100

Util

izat

ion

ratio




10 20 30 40 50 60 70 80 90 100 110 1200Time (min)

01234

Que

ue le

ngth




Automobile yard

Express cargo yard

Container yard



Special cargo yard

Bulky cargo yard


Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l


09

092

094

096

098

1

102

104










1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia






3 Framework Design






Special cargo yard


Container yard

Bulk cargo yard

①


Special cargo yard


Container yard

Bulk cargo yard

②


Special cargo yard


Container yard

Bulk cargo yard

③


Special cargo yard


Container yard

Bulk cargo yard

④
















Entrance gate

Exit gate



Cargo yard

Cargo yard

Parkingarea




Layoutlayer




User interfaces



Simulatorlayer

Simulation module







Petri Netlayer














4 Simulation Model


TPN = (119875 119879PrePost 119865) (1)







R3

R2 R1















key points

Train waiting queue

Stop

No

No

Yes

Yes
















T1 T2 T3 T4 T5 T6 T7 T8 T9

T10

T11 T12 T13 T14 T15 T16 T17 T18 T19

T20 T21

T22

T23

T24 T25 T26

T27 T28 T29

T32

T30

T33

T34 T35

T36

T37

T38 T39 T40

T41 T42 T43 T44

T46

P1 P3 P4P2P5

P6

P7

P8

P9

P10

P11P12

P13P14

P15

P16 P17 P18 P19 P20 P21

P15

P23

P24

P25

P37

P26

P27 P28 P29P30P31

P32P33

P34 P35

P36P38

P39

P40

P41

P42 P43 P44

P46

P45

P47 P48 P49 P50 P51

P52

P54

P55

P56

P57

P58

P59 P60 P61

P62

P63

P64 P65 P66 P67 P68

P69

P71

T47

P72

P53

T31

P70

T45




P22






























151 2 25 3 35 4 45 5 55 6 6505Dwell time (h)

020406080

Trai

ns

(a)


Bulk

carg

o ya

rd

Lugg

age e

xpre

ss y

ard

Con

tain

er y

ard

Bulk

y ca

rgo

yard

Expr

ess c

argo

yar

d

Auto

mob

ile y

ard

Spec

ial c

argo

yar

d

02468

10

Tim

e (h)

(b)

Con

tain

er y

ard

Bulk

carg

o ya

rd

Auto

mob

ile y

ard

Lugg

age e

xpre

ss y

ard

Bulk

y ca

rgo

yard

Spec

ial c

argo

yar

d

Expr

ess c

argo

yar

d

002040608

112

Tim

e (h)




12 24 36 48 60 72 84 96 108 1200Time (h)

0

20

40

60

80

100

Util

izat

ion

ratio




10 20 30 40 50 60 70 80 90 100 110 1200Time (min)

01234

Que

ue le

ngth




Automobile yard

Express cargo yard

Container yard



Special cargo yard

Bulky cargo yard


Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l


09

092

094

096

098

1

102

104










1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



Special cargo yard


Container yard

Bulk cargo yard

①


Special cargo yard


Container yard

Bulk cargo yard

②


Special cargo yard


Container yard

Bulk cargo yard

③


Special cargo yard


Container yard

Bulk cargo yard

④
















Entrance gate

Exit gate



Cargo yard

Cargo yard

Parkingarea




Layoutlayer




User interfaces



Simulatorlayer

Simulation module







Petri Netlayer














4 Simulation Model


TPN = (119875 119879PrePost 119865) (1)







R3

R2 R1















key points

Train waiting queue

Stop

No

No

Yes

Yes
















T1 T2 T3 T4 T5 T6 T7 T8 T9

T10

T11 T12 T13 T14 T15 T16 T17 T18 T19

T20 T21

T22

T23

T24 T25 T26

T27 T28 T29

T32

T30

T33

T34 T35

T36

T37

T38 T39 T40

T41 T42 T43 T44

T46

P1 P3 P4P2P5

P6

P7

P8

P9

P10

P11P12

P13P14

P15

P16 P17 P18 P19 P20 P21

P15

P23

P24

P25

P37

P26

P27 P28 P29P30P31

P32P33

P34 P35

P36P38

P39

P40

P41

P42 P43 P44

P46

P45

P47 P48 P49 P50 P51

P52

P54

P55

P56

P57

P58

P59 P60 P61

P62

P63

P64 P65 P66 P67 P68

P69

P71

T47

P72

P53

T31

P70

T45




P22






























151 2 25 3 35 4 45 5 55 6 6505Dwell time (h)

020406080

Trai

ns

(a)


Bulk

carg

o ya

rd

Lugg

age e

xpre

ss y

ard

Con

tain

er y

ard

Bulk

y ca

rgo

yard

Expr

ess c

argo

yar

d

Auto

mob

ile y

ard

Spec

ial c

argo

yar

d

02468

10

Tim

e (h)

(b)

Con

tain

er y

ard

Bulk

carg

o ya

rd

Auto

mob

ile y

ard

Lugg

age e

xpre

ss y

ard

Bulk

y ca

rgo

yard

Spec

ial c

argo

yar

d

Expr

ess c

argo

yar

d

002040608

112

Tim

e (h)




12 24 36 48 60 72 84 96 108 1200Time (h)

0

20

40

60

80

100

Util

izat

ion

ratio




10 20 30 40 50 60 70 80 90 100 110 1200Time (min)

01234

Que

ue le

ngth




Automobile yard

Express cargo yard

Container yard



Special cargo yard

Bulky cargo yard


Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l


09

092

094

096

098

1

102

104










1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



Entrance gate

Exit gate



Cargo yard

Cargo yard

Parkingarea




Layoutlayer




User interfaces



Simulatorlayer

Simulation module







Petri Netlayer














4 Simulation Model


TPN = (119875 119879PrePost 119865) (1)







R3

R2 R1















key points

Train waiting queue

Stop

No

No

Yes

Yes
















T1 T2 T3 T4 T5 T6 T7 T8 T9

T10

T11 T12 T13 T14 T15 T16 T17 T18 T19

T20 T21

T22

T23

T24 T25 T26

T27 T28 T29

T32

T30

T33

T34 T35

T36

T37

T38 T39 T40

T41 T42 T43 T44

T46

P1 P3 P4P2P5

P6

P7

P8

P9

P10

P11P12

P13P14

P15

P16 P17 P18 P19 P20 P21

P15

P23

P24

P25

P37

P26

P27 P28 P29P30P31

P32P33

P34 P35

P36P38

P39

P40

P41

P42 P43 P44

P46

P45

P47 P48 P49 P50 P51

P52

P54

P55

P56

P57

P58

P59 P60 P61

P62

P63

P64 P65 P66 P67 P68

P69

P71

T47

P72

P53

T31

P70

T45




P22






























151 2 25 3 35 4 45 5 55 6 6505Dwell time (h)

020406080

Trai

ns

(a)


Bulk

carg

o ya

rd

Lugg

age e

xpre

ss y

ard

Con

tain

er y

ard

Bulk

y ca

rgo

yard

Expr

ess c

argo

yar

d

Auto

mob

ile y

ard

Spec

ial c

argo

yar

d

02468

10

Tim

e (h)

(b)

Con

tain

er y

ard

Bulk

carg

o ya

rd

Auto

mob

ile y

ard

Lugg

age e

xpre

ss y

ard

Bulk

y ca

rgo

yard

Spec

ial c

argo

yar

d

Expr

ess c

argo

yar

d

002040608

112

Tim

e (h)




12 24 36 48 60 72 84 96 108 1200Time (h)

0

20

40

60

80

100

Util

izat

ion

ratio




10 20 30 40 50 60 70 80 90 100 110 1200Time (min)

01234

Que

ue le

ngth




Automobile yard

Express cargo yard

Container yard



Special cargo yard

Bulky cargo yard


Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l


09

092

094

096

098

1

102

104










1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia







4 Simulation Model


TPN = (119875 119879PrePost 119865) (1)







R3

R2 R1















key points

Train waiting queue

Stop

No

No

Yes

Yes
















T1 T2 T3 T4 T5 T6 T7 T8 T9

T10

T11 T12 T13 T14 T15 T16 T17 T18 T19

T20 T21

T22

T23

T24 T25 T26

T27 T28 T29

T32

T30

T33

T34 T35

T36

T37

T38 T39 T40

T41 T42 T43 T44

T46

P1 P3 P4P2P5

P6

P7

P8

P9

P10

P11P12

P13P14

P15

P16 P17 P18 P19 P20 P21

P15

P23

P24

P25

P37

P26

P27 P28 P29P30P31

P32P33

P34 P35

P36P38

P39

P40

P41

P42 P43 P44

P46

P45

P47 P48 P49 P50 P51

P52

P54

P55

P56

P57

P58

P59 P60 P61

P62

P63

P64 P65 P66 P67 P68

P69

P71

T47

P72

P53

T31

P70

T45




P22






























151 2 25 3 35 4 45 5 55 6 6505Dwell time (h)

020406080

Trai

ns

(a)


Bulk

carg

o ya

rd

Lugg

age e

xpre

ss y

ard

Con

tain

er y

ard

Bulk

y ca

rgo

yard

Expr

ess c

argo

yar

d

Auto

mob

ile y

ard

Spec

ial c

argo

yar

d

02468

10

Tim

e (h)

(b)

Con

tain

er y

ard

Bulk

carg

o ya

rd

Auto

mob

ile y

ard

Lugg

age e

xpre

ss y

ard

Bulk

y ca

rgo

yard

Spec

ial c

argo

yar

d

Expr

ess c

argo

yar

d

002040608

112

Tim

e (h)




12 24 36 48 60 72 84 96 108 1200Time (h)

0

20

40

60

80

100

Util

izat

ion

ratio




10 20 30 40 50 60 70 80 90 100 110 1200Time (min)

01234

Que

ue le

ngth




Automobile yard

Express cargo yard

Container yard



Special cargo yard

Bulky cargo yard


Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l


09

092

094

096

098

1

102

104










1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia







key points

Train waiting queue

Stop

No

No

Yes

Yes
















T1 T2 T3 T4 T5 T6 T7 T8 T9

T10

T11 T12 T13 T14 T15 T16 T17 T18 T19

T20 T21

T22

T23

T24 T25 T26

T27 T28 T29

T32

T30

T33

T34 T35

T36

T37

T38 T39 T40

T41 T42 T43 T44

T46

P1 P3 P4P2P5

P6

P7

P8

P9

P10

P11P12

P13P14

P15

P16 P17 P18 P19 P20 P21

P15

P23

P24

P25

P37

P26

P27 P28 P29P30P31

P32P33

P34 P35

P36P38

P39

P40

P41

P42 P43 P44

P46

P45

P47 P48 P49 P50 P51

P52

P54

P55

P56

P57

P58

P59 P60 P61

P62

P63

P64 P65 P66 P67 P68

P69

P71

T47

P72

P53

T31

P70

T45




P22






























151 2 25 3 35 4 45 5 55 6 6505Dwell time (h)

020406080

Trai

ns

(a)


Bulk

carg

o ya

rd

Lugg

age e

xpre

ss y

ard

Con

tain

er y

ard

Bulk

y ca

rgo

yard

Expr

ess c

argo

yar

d

Auto

mob

ile y

ard

Spec

ial c

argo

yar

d

02468

10

Tim

e (h)

(b)

Con

tain

er y

ard

Bulk

carg

o ya

rd

Auto

mob

ile y

ard

Lugg

age e

xpre

ss y

ard

Bulk

y ca

rgo

yard

Spec

ial c

argo

yar

d

Expr

ess c

argo

yar

d

002040608

112

Tim

e (h)




12 24 36 48 60 72 84 96 108 1200Time (h)

0

20

40

60

80

100

Util

izat

ion

ratio




10 20 30 40 50 60 70 80 90 100 110 1200Time (min)

01234

Que

ue le

ngth




Automobile yard

Express cargo yard

Container yard



Special cargo yard

Bulky cargo yard


Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l


09

092

094

096

098

1

102

104










1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia







T1 T2 T3 T4 T5 T6 T7 T8 T9

T10

T11 T12 T13 T14 T15 T16 T17 T18 T19

T20 T21

T22

T23

T24 T25 T26

T27 T28 T29

T32

T30

T33

T34 T35

T36

T37

T38 T39 T40

T41 T42 T43 T44

T46

P1 P3 P4P2P5

P6

P7

P8

P9

P10

P11P12

P13P14

P15

P16 P17 P18 P19 P20 P21

P15

P23

P24

P25

P37

P26

P27 P28 P29P30P31

P32P33

P34 P35

P36P38

P39

P40

P41

P42 P43 P44

P46

P45

P47 P48 P49 P50 P51

P52

P54

P55

P56

P57

P58

P59 P60 P61

P62

P63

P64 P65 P66 P67 P68

P69

P71

T47

P72

P53

T31

P70

T45




P22






























151 2 25 3 35 4 45 5 55 6 6505Dwell time (h)

020406080

Trai

ns

(a)


Bulk

carg

o ya

rd

Lugg

age e

xpre

ss y

ard

Con

tain

er y

ard

Bulk

y ca

rgo

yard

Expr

ess c

argo

yar

d

Auto

mob

ile y

ard

Spec

ial c

argo

yar

d

02468

10

Tim

e (h)

(b)

Con

tain

er y

ard

Bulk

carg

o ya

rd

Auto

mob

ile y

ard

Lugg

age e

xpre

ss y

ard

Bulk

y ca

rgo

yard

Spec

ial c

argo

yar

d

Expr

ess c

argo

yar

d

002040608

112

Tim

e (h)




12 24 36 48 60 72 84 96 108 1200Time (h)

0

20

40

60

80

100

Util

izat

ion

ratio




10 20 30 40 50 60 70 80 90 100 110 1200Time (min)

01234

Que

ue le

ngth




Automobile yard

Express cargo yard

Container yard



Special cargo yard

Bulky cargo yard


Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l


09

092

094

096

098

1

102

104










1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia























151 2 25 3 35 4 45 5 55 6 6505Dwell time (h)

020406080

Trai

ns

(a)


Bulk

carg

o ya

rd

Lugg

age e

xpre

ss y

ard

Con

tain

er y

ard

Bulk

y ca

rgo

yard

Expr

ess c

argo

yar

d

Auto

mob

ile y

ard

Spec

ial c

argo

yar

d

02468

10

Tim

e (h)

(b)

Con

tain

er y

ard

Bulk

carg

o ya

rd

Auto

mob

ile y

ard

Lugg

age e

xpre

ss y

ard

Bulk

y ca

rgo

yard

Spec

ial c

argo

yar

d

Expr

ess c

argo

yar

d

002040608

112

Tim

e (h)




12 24 36 48 60 72 84 96 108 1200Time (h)

0

20

40

60

80

100

Util

izat

ion

ratio




10 20 30 40 50 60 70 80 90 100 110 1200Time (min)

01234

Que

ue le

ngth




Automobile yard

Express cargo yard

Container yard



Special cargo yard

Bulky cargo yard


Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l


09

092

094

096

098

1

102

104










1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



Automobile yard

Express cargo yard

Container yard



Special cargo yard

Bulky cargo yard


Expr

ess

Bulk

y

Gra

in Car

Con

tain

er

Iron

Spec

ial

Tota

l


09

092

094

096

098

1

102

104










1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




1000

2000

3000

4000

5000

6000

Util

izat

ion

ratio

()




Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25





Nor

mal

ized

load

ing

unlo

adin

g tim

e

50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 80000

05

1

15

2

25


Dwell time


0

500

1000

1500

2000

2500

3000

Freq

uenc

y







Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia





Express cargo 119863(119876) 0012944 0011589 0018251 0008871119864(119876) 050 094 181 175

Bulky cargo 119863(119876) 0016761 0035432 0015348 0015244119864(119876) 065 098 153 152

Grain crops 119863(119876) 0020680 0022395 0021014 0012596119864(119876) 082 070 210 126

Automobile 119863(119876) 0011556 0015392 0000179 0048468119864(119876) 080 059 002 383

Container 119863(119876) 0011646 0012187 0000863 0003889119864(119876) 022 101 009 153

Iron products 119863(119876) 0012918 0020601 0014844 0003483119864(119876) 092 162 148 188

Special cargo 119863(119876) 0011461 0019520 0010384 0034711119864(119876) 069 170 104 347



0

500

1000

1500

2000

2500

3000

Freq

uenc

y



119863 (119876) = 1119899119899sum119894=1

1003816100381610038161003816119876119904 (119894) minus 119876ℎ1003816100381610038161003816119876ℎ (2)

119864 (119876) = 10038161003816100381610038161003816100381610038161003816100381610038161 minus (1119899119899sum119894=1

119876119904 (119894)119876119904 )1003816100381610038161003816100381610038161003816100381610038161003816 sdot 100 (3)










Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia





Receiving lines




E1

L1

L2

(a) Scheme A

Grain yard


Receiving lines

Departure lines




E1

L1

L2

(b) Scheme B









597694 658

344 324



000

200

400

600

800

()






820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




820 767


minus400

minus200

000

200

400

600

800

1000

()














075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



075 100 125 150050


040

060

080

100

120

140

160

180La

ytim

e of t

rain

s






050

075

100

125

150

Layt

ime o

f tru

cks

075 100 125050 150




000

050

100

150

200

250

300

Wai

t tim

e for

load

ing

unlo

adin

g of

trai

ns





050

100

150

200

250

Wai

t tim

e for

load

ing

unlo

adin

gof

truc

ks

075 100 125 150050














Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia






Acknowledgments


References
































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia










RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia


A Simulation Platform for Combined Rail/Road...

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Transcript of A Simulation Platform for Combined Rail/Road...