A simulation optimization method that considers uncertainty and multiple performance measures

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24 Scopus citations


Simulation optimization provides a structured approach to system design and configuration when analytical expressions for input/output relationships are unavailable. This research focuses on the development of a new simulation optimization technique applicable to systems having multiple performance measures. The aim of this research is to incorporate a simulation end user's preference towards risk and uncertainty into the search process for the best decision alternative. Automation of the optimization procedure is a necessity. Therefore, this paper proposes a simulation optimization method that involves a preference model, specifically adapted for decision making with simulation models. The proposed simulation optimization method is evaluated against two simulation optimization methods with embedded deterministic, multiple criteria decision making strategies. It is shown on average to obtain significantly better solutions in multiple types of experimental settings having normally distributed simulation performance measures.

Original languageEnglish (US)
Pages (from-to)315-330
Number of pages16
JournalEuropean Journal of Operational Research
Issue number1
StatePublished - Aug 16 2007

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


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