Simulation modeling for analysis

  • Authors:
  • Lee Schruben

  • Affiliations:
  • University of California, Berkeley, CA

  • Venue:
  • ACM Transactions on Modeling and Computer Simulation (TOMACS)
  • Year:
  • 2010

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Abstract

This article explores possibilities for designing and executing simulation models with specific analysis goals in mind, and shows that a tight coupling of the modeling and analysis phases in a simulation project can lead to dramatic improvements in the study results. Suggestions are made for how simulation analysis, considered in the explicit context of discrete-event simulation models, can create new opportunities for meaningful research and more efficient modeling. Modeling decisions can play a significant role in the performance of analytical procedures. How a simulation model is designed can enable, inhibit, or even invalidate analytical procedures and methodology research results.