18s Simulation McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc All Learning Objectives Explain what is meant by the term simulation List some of the reasons for simulation’s popularity as a tool for decision making Explain how and why random numbers are used are used in simulation Outline the advantages and limitations of simulation Describe the alternatives that a manager would reject before choosing simulation as a decision making tool Solve typical problems that require simulation 18S-2 Simulation 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-3 Simulation Process Identify the problem Develop the simulation model Test the model Develop the experiments Run the simulation and evaluate results Repeat and until results are satisfactory 18S-4 Monte 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-5 Example S-1 18S-6 Example S-1 18S-7 Simulating Distributions Poisson Mean of distribution is required Normal Need to know the mean and standard deviation Simulated = Mean value + Random X Standard number deviation 18S-8 Figure 18S.1 Uniform Distribution F(x) a b x Simulated a + (b - a)(Random number as a percentage) = value 18S-9 Negative Exponential Distribution Figure 18S.2 F(t) P ( t ≥ T ) = RN T t 18S-10 Computer Simulation Simulation languages SIMSCRIPT II.5 GPSS/H GPSS/PC RESQ 18S-11 Advantages 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-12 Limitations 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 18S-13 ...Learning Objectives Explain what is meant by the term simulation List some of the reasons for simulation’s popularity as a tool for decision