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Simulation Modeling


Linda Friedman


Every phase of a simulation study is examined in detail:  problem definition, data collection, model building, model validation, experimental design, simulation, output analysis.  Close attention is paid to the simulation experimental design, including such concerns as sample size/run-length determination and variance reduction.  Simulation assignments, including a term project, may be coded in a general language such as C++ or in a special-purpose language such as ARENA or SIMSCRIPT.  Case studies, such as inventory systems, hospital systems, manufacturing, telecommunication, public policy, and / or large scale models, are discussed.


Topic List

Topics may include but are not limited to:

  • Modeling Concepts

  • Simulation Programming in SIMSCRIPT

    • Data Structures for Simulation.
    • Modeling Random Phenomena.
    • Reporting Statistics.
    • Simulating Over Time.
  • Selecting the Input Data Probability Distribution

  • Tools For Simulating Dynamic Models

  • Designing the Simulation Experiment

  • Statistical Analysis of Simulation Output

  • Validation & Verification of Simulation Models

Course Objectives:

The primary learning objective of this course is to develop students’ analytic skills, particularly as applied to system simulation experiments.  Students will gain practical experience with a widely-used simulation programming language.  They will work individually or in small groups, and follow several simulation projects through to completion.


  • Homework 1: 20%

  • Homework 2: 20%

  • Homework 3: 25%

  • Term project: 35%