7-1 Transport Decisions CR (2004) Prentice Hall, Inc. Chapter 7 If you are planning for one year,...
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Transcript of 7-1 Transport Decisions CR (2004) Prentice Hall, Inc. Chapter 7 If you are planning for one year,...
7-1
Transport Decisions
CR (2004) Prentice Hall, Inc.
Chapter 7
If you are planning for one year, grow rice. If you are planning for 20 years, grow trees. If you are planning for centuries, grow men.
A Chinese proverb
7-2
Transport Decisionsin Transport Strategy
PL
AN
NIN
G
OR
GA
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CO
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RO
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Transport Strategy• Transport fundamentals• Transport decisions
Customer service goals
• The product• Logistics service• Ord. proc. & info. sys.
Inventory Strategy• Forecasting• Inventory decisions• Purchasing and supply
scheduling decisions• Storage fundamentals• Storage decisions
Location Strategy• Location decisions• The network planning process
PL
AN
NIN
G
OR
GA
NIZ
ING
CO
NT
RO
LL
ING
Transport Strategy• Transport fundamentals•Transport decisions
Customer service goals
• The product• Logistics service• Ord. proc. & info. sys.
Inventory Strategy• Forecasting• Inventory decisions• Purchasing and supply
scheduling decisions• Storage fundamentals• Storage decisions
Location Strategy• Location decisions• The network planning process
CR (2004) Prentice Hall, Inc.
7-3
Just a few of the many problems in transportation
Typical Transport Decisions
CR (2004) Prentice Hall, Inc.
Mode/Service selection Private fleet planning
- Carrier routing - Routing from multiple points - Routing from coincident origin-destination
points - Vehicle routing and scheduling
Freight consolidation
7-4
Mode/Service Selection
CR (2004) Prentice Hall, Inc.
The problem Define the available choices Balance performance effects on inventory against
the cost of transport Methods for selection
Indirectly through network configuration Directly through channel simulation Directly through a spreadsheet approach as follows:
Alternatives Cost types Air Truck Rail Transportation In-transit inventory Source inventory Destination inventory
7-5
Mode/Service Selection (Cont’d)Example Finished goods are to be shipped from a plant inventory to a warehouse inventory some distance away. The expected volume to be shipped in a year is 1,200,000 lb. The product is worth $25 per lb. and the plant and carrying costs are 30% per year.
Other data are:
CR (2004) Prentice Hall, Inc.
Transport choice
Rate, $/lb.
Transit time, days
Shipment size, lb.
Rail 0.11 25 100,000
Truck 0.20 13 40,000
Air 0.88 1 16,000
Include transport rate
Transport Selection AnalysisCosttype
Compu-tation Rail Truck Air
Trans-portation
RD .11(1,200,000)= $132,000
.20(1,200,000)= $240,000
.88(1,200,000)= $1,056,000
In-transitinventory
ICDT
365[.30(25)1,200,000(25)]/365= $616,438
[.30(25) 1,200,000(13)]/365= $320,548
[.30(25) 1,200,000(1)]/365= $24,658
Plantinventory
ICQ
2[.30(25) 100,000]/2= $375,000
[.30(25) 40,000]/2= $150,000
[.30(25) 16,000]/2= $60,000
Whseinventory
IC'Q2
[.30(25.11) 100,000]/2= $376,650
[.30(25.20) 40,000]/2= $151,200
[.30(25.88) 16,000]/2= $62,112
Totals $1,500,088 $ 861,748 $1,706,770
Improved serviceCR (2004) Prentice Hall, Inc. 7-6
7-7
Carrier Routing Determine the best path between origin and destination points over a
network of routes
Shortest route method is efficient for finding the minimal cost route
Consider a time network between Amarillo and Fort Worth. Find the minimum travel time.
The procedure can be paraphrased as:
Find the closest unsolved node to a solved node
Calculate the cost to the unsolved node by adding the accumulated cost to the solved node to the cost from the solved node to the unsolved node.
Select the unsolved node with the minimum time as the new solved node. Identify the link.
When the destination node is solved, the computations stop. The solution is found by backtracking through the connections made.
CR (2004) Prentice Hall, Inc.
7-8
OriginAmarillo
OklahomaCity
DestinationFort Worth
AB E
I
C
D G
F
H
J
90 minutes 84 84
138
348
156
48
132
150
126
13212066
126
48
60
Note: All link times are in minutes
90
Carrier Routing (Cont’d)
Can be a weighted index of time and distance
CR (2004) Prentice Hall, Inc.
7-9
Sh
ort
est
Ro
ute
Met
ho
d
CR (2004) Prentice Hall, Inc.
Step
Solved Nodes
Directly Connected to Unsolved
Nodes
Its Closest Connected Unsolved
Node
Total Cost Involved
nth Nearest
Node
Its Minimum Cost
Its Last Connection a
1 A B 90 B 90 AB* 2 A C 138 C 138 AC B C 90+66=156
3 A D 348 B E 90+84=174 E 174 BE* C F 138+90=228
4 A D 348 C F 138+90=228 F 228 CF E I 174+84=258
5 A D 348 C D 138+156=294 E I 174+84=258 I 258 EI* F H 228+60=288
6 A D 348 C D 138+156=294 F H 228+60=288 H 288 FH I J 258+126=384
7 A D 348 C D 138+156=294 D 294 CD F G 288+132=360 H G 288+48=336 I J 258+126=384
8 H J 288+126=414 I J 258+126=384 J 384 IJ*
7-10
MAPQUEST SOLUTION
Mapquest at www.mapquest.com
CR (2004) Prentice Hall, Inc.
7-11
Plant 1Requirements = 600
Plant 2Requirements = 500
Plant 3Requirements = 300
Supplier ASupply 400
Supplier CSupply 500
Supplier BSupply 700
4a
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5
5
5
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5
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aThe transportation rate in $ per ton for an optimal routing between supplier A and plant 1.
Routing from Multiple PointsThis problem is solved by the traditional transportation method of linear programming
CR (2004) Prentice Hall, Inc.
7-12
TRANLP problem setup
Solution
CR (2004) Prentice Hall, Inc.
7-13
Routing with a Coincident Origin/Destination Point
D DDepot Depot
(a) Poor routing-- paths cross
(b) Good routing-- no paths cross
Typical of many single truck routing problems from a single depot.
Mathematically, a complex problem to solve efficiently. However, good routes can be found by forming a route pattern where the paths do not cross a "tear drop" pattern.
CR (2004) Prentice Hall, Inc.
Single Route Developed by ROUTESEQ in LOGWARE
0 1 2 3 4 5 6 7 8
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X coordinates
1
2
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D
Y coordinates
0 1 2 3 4 5 6 7 8
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X coordinates
1
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19
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Y coordinates
(a) Location of beverage accountsand distribution center (D) withgrid overlay
(b) Suggested routing pattern
CR (2004) Prentice Hall, Inc.7-14
7-15
Multi-Vehicle Routing and Scheduling
A problem similar to the single-vehicle routing problem except that a number of restrictions are placed on the problem. Chief among these are:
- A mixture of vehicles with different capacities - Time windows on the stops - Pickups combined with deliveries - Total travel time for a vehicle
CR (2004) Prentice Hall, Inc.
7-16
Practical Guidelines for Good Routing and Scheduling
1. Load trucks with stop volumes that are in closest proximity to each other
(a) Weak clustering
Depot
(b) Better clustering
D DDepot
Stops
CR (2004) Prentice Hall, Inc.
7-17
Guidelines (Cont’d)
2. Stops on different days should be arranged to produce tight clusters
F
F
F
F
F
F
F
T
T T
T
T
T
T
DDepot
F
F
F
F
F
T
T
T
F T
F
T
T
T
DDepot
(a) Weak clustering--routes cross
(b) Better clustering
Stop
May need to coordinate with sales to achieve
clusters
CR (2004) Prentice Hall, Inc.
7-18
Guidelines (Cont’d)3. Build routes beginning with the farthest stop from the depot
4. The stop sequence on a route should form a teardrop pattern (without time windows)
5. The most efficient routes are built using the largest vehicles available first
6. Pickups should be mixed into delivery routes rather than assigned to the end of the routes
7. A stop that is greatly removed from a route cluster is a good candidate for an alternate means of delivery
8. Narrow stop time window restrictions should be avoided (relaxed)
7-19
Application of Guidelines to Casket Distribution
WarehouseFuneral home Typical weekly demand
and pickupsCR (2004) Prentice Hall, Inc.
7-20
Application of Guidelines to Casket Distribution (Cont’d)
WarehouseFuneral home
Division of sales territories into days of the week
Territories of equal size
to minimize number of trucks
CR (2004) Prentice Hall, Inc.
7-21
Application of Guidelines to Casket Distribution (Cont’d)
WarehouseFuneral home Route design within territories
CR (2004) Prentice Hall, Inc.
7-22
“Sweep” Method for VRP
Example A trucking company has 10,000-unit vans for merchandise pickup to be consolidated into larger loads for moving over long distances. A day’s pickups are shown in the figure below. How should the routes be designed for minimal total travel distance?
CR (2004) Prentice Hall, Inc.
7-23
Geographicalregion
Depot
1,000
2,0003,000
2,000
4,000
2,000
3,000 3,000
1,000
2,0002,000
2,000
Pickuppoints
Stop Volume and Location
CR (2004) Prentice Hall, Inc.
7-24
Sweep directionis arbitrary
Depot
1,000
2,0003,000
2,000
4,000
2,000
3,000 3,000
1,000
2,0002,000
2,000
Route #110,000 units
Route #29,000 units
Route #38,000 units
“Sweep” Method Solution
CR (2004) Prentice Hall, Inc.
The “Savings” Method for VRP
Depot Depot
(a) Initial routing Route distance = d0,A +dA,0 +d0,B+ dB,0
(b) Combining two stops on a route Route distance = d 0,A +dA,B +dB,0
A
B
dA,0
d0,Ad0,B
dB,0
A
BdB,0
d0,A
dA,B
Stop
Stop
0 0
“Savings” is better than “Sweep” method—has lower average error
CR (2004) Prentice Hall, Inc.7-25
7-26
Savings Method Observation
The points that offer the greatest savings when combined on the same route are those that are farthest from the depot and that are closest to each other.
This is a good principle for constructing multiple-stop
routes
CR (2004) Prentice Hall, Inc.
Route Sequencing in VRP
8 9 10 11 12 1 2 3 4 5 6Route #1 Route #10
AM PM
Route #6
Route #9 Route #4
Route #5 Route #8
Route #2 Route #7
Route #3
Truck #1
Truck #2
Truck #3
Truck #4
Truck #5
Minimize number of trucks by maximizing number of routes
handled by a single truckCR (2004) Prentice Hall, Inc. 7-27
7-28
Freight Consolidation
Combine small shipments into larger ones
A problem of balancing cost savings against customer service reductions
An important area for cost reduction in many firms
Based on the rate-shipment size relationship for for-hire carriers
CR (2004) Prentice Hall, Inc.
7-29
Freight Consolidation Analysis
CR (2004) Prentice Hall, Inc.
Suppose we have the following orders for the next three days.
Consider shipping these orders each day or consolidating them into one shipment. Suppose that we know the transport rates.
Note: Rates from an interstate tariff
From: Ft Worth Day 1 Day 2 Day 3 To: Topeka 5,000 lb. 25,000 lb. 18,000 lb. Kansas City 7,000 12,000 21,000 Wichita 42,000 38,000 61,000
Freight Consolidation Analysis (Cont’d) Day 1 Day 2
Rate x volume = cost Rate x volume = cost
Topeka 3.42 x 50 = $171.00 1.14 x 250 = $285.00
Kansas City 3.60 x 70 = 252.00 1.44 x 120 = 172.80
Wichita 0.68 x 420 = 285.60 0.68 x 400a = 272.00
Total $708.60 Total $729.80a Ship 380 cwt., as if full truckload of 400 cwt.
Day 3 Totals
Rate x volume = cost
Topeka 1.36 x 180 = $244.80 $700.80
Kansas City 1.20 x 210 = 252.00 676.80
Wichita 0.68 x 610 = 414.80 972.40
Total $911.60 $2,350.00
Separate shipments
CR (2004) Prentice Hall, Inc. 7-30
Freight Consolidation Analysis (Cont’d)
a 480 = 50 + 250 + 180
Computing transport cost for one combined, three-day shipment
Cheaper, but what aboutthe service effects of holdingearly orders for a longer timeto accumulate larger shipmentsizes?
Consolidated shipment
Day 3 Rate x volume = cost
Topeka 0.82 x 480a = $393.60
Kansas City 0.86 x 400 = 344.00
Wichita 0.68 x 1410 = 958.80
Total $1,696.40
CR (2004) Prentice Hall, Inc. 7-31