18s-1 Simulation

William J. Stevenson

Operations Management

8th edition

18s-2 Simulation

CHAPTER18s

Simulation

McGraw-Hill/IrwinOperations Management, Eighth Edition, by William J. StevensonCopyright © 2005 by The McGraw-Hill Companies, Inc. All rights

reserved.

18s-3 Simulation

SimulationSimulation

Simulation: a descriptive technique that enables a decision maker to evaluate the behavior of a model under various conditions.

Simulation models complex situations

Models are simple to use and understand

Models can play “what if” experiments

Extensive software packages available

18s-4 Simulation

Simulation ProcessSimulation Process

1. Identify the problem

2. Develop the simulation model

3. Test the model

4. Develop the experiments

5. Run the simulation and evaluate results

6. Repeat 4 and 5 until results are satisfactory

18s-5 Simulation

Monte Carlo SimulationMonte Carlo Simulation

Monte Carlo method: Probabilistic simulation technique used when a process has a random component

Identify a probability distribution

Setup intervals of random numbers to match probability distribution

Obtain the random numbers Interpret the results

18s-6 Simulation

Example S-1Example S-1

18s-7 Simulation

Example S-1Example S-1

18s-8 Simulation

Simulating DistributionsSimulating Distributions

Poisson Mean of distribution is required

Normal Need to know the mean and standard

deviation

Simulatedvalue

Mean Randomnumber

Standarddeviation

+ X=

18s-9 Simulation

Uniform DistributionUniform Distribution

a b0 x

F(x)

Simulatedvalue

a + (b - a)(Random number as a percentage)=

Figure 18S.1

18s-10 Simulation

Negative Exponential DistributionNegative Exponential DistributionFigure 18S.2

F(t)

0 T t

P t T RN( ) .

18s-11 Simulation

Computer SimulationComputer Simulation

Simulation languages

SIMSCRIPT II.5

GPSS/H

GPSS/PC

RESQ

18s-12 Simulation

Advantages of SimulationAdvantages of Simulation

Solves problems that are difficult or impossible to solve mathematically

Allows experimentation without risk to actual system

Compresses time to show long-term effects

Serves as training tool for decision makers

18s-13 Simulation

Limitations of SimulationLimitations of Simulation

Does not produce optimum solution

Model development may be difficult

Computer run time may be substantial

Monte Carlo simulation only applicable to random systems