Simulation with Arena

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New Modeling Issues• Service rather than manufacturing system — canstill use many of the same ideas, constructs• More complex — need more detailed modeling• Nonstationary arrival process– Often need to represent it for model validity– Appealing (but wrong) approach• Keep track of current arrival rate• Generate next interarrival as EXPO [1/(current arrival rate)]• See text for explanation of why this is wrong– Useful probabilistic model: Nonstationary Poisson Process(NSPP)Simulation with Arena — Chapter 8 — Detailed Modeling 8 - 12
Nonstationary Poisson Process• Calls arrive one at a time, independently, but atan expected rate that can vary over time• Number of calls in a time interval ~ Poissonrandom variable with mean = area under ratefunction during the time interval• Assume piecewise-constant rate function fromdata table (but form could be anything)• One way to generate NSPP correctly: ThinningSimulation with Arena — Chapter 8 — Detailed Modeling 8 - 13
Page 1 and 2: Chapter 8Detailed Modeling
Page 3 and 4: Model 8.1: A Generic Call CenterSys
Page 5 and 6: Technical Support Calls (cont’d.)
Page 7 and 8: Order-Status Calls• Automatically
Page 9 and 10: Staffing• All employees work 8-ho
Page 11: Key Output PerformanceMeasures• C
Page 15 and 16: Balking• Calls arriving when all
Page 17 and 18: Statistical and Analysis Needs• T
Page 19 and 20: Terminating or Steady-State• Ofte
Page 21 and 22: Defining the Data• Collect data m
Page 23 and 24: Defining the Data (cont’d.)• Ex
Page 25 and 26: Increment Time Period (cont’d.)
Page 27 and 28: Create Arrivals and Direct toServic
Page 29 and 30: Technical Support Calls• Lots of
Page 31 and 32: Technical Support Calls (cont’d.)
Page 33 and 34: Order-Status Calls• Initially don
Page 35 and 36: Finding and Fixing Model Errors(con
Page 37 and 38: Animating the Model (cont’d.)•

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