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Areas Of Simulation Application
Waiting lines/service Inventory management Production & manufacturing systems Supply chain systems Service operations Environmental & resource analysis
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Building a Simulation Model
Define the problem, objectives and variables Random variables (source of uncertainty) Decision variables Create a model to represent the problem Design the logic between the variables (formulas, flowcharts) Collect data for the probability distributions Create a computer program or template
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Building a Simulation Model (continued)
Validate the model Check formulas and logic especially in copied rows Design “what-if” strategies for the decision variables Run the model MANY times for each possible “what-if” strategy to see what would happen on average, in the worst case as well as in the best case scenario.
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Monte Carlo Simulation
Use random numbers that have an equal likelihood of being selected (lottery balls) to select numbers from a probability distribution Use these values to observe how a model of a system performs over time
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Distribution Of Demand
Cases demanded Frequency of Probability of per week, x Demand Demand P(x)
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Roulette Wheel Of Demand
90 x = 18 x = 14 20 80 x = 17 x = 16 x = 15 60
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Russell/Taylor Oper Mgt 3/e
Random Number Table © 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e
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Generating Demand From Random Numbers
Demand Ranges of Random Numbers x r r = 39
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15 Weeks Of Demand Average demand = 241/15 = 16.1 cases per week
Week r Demand (x) Week r Demand (x) = 241 Average demand = 241/15 = 16.1 cases per week
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