A survey of simulation optimization techniques and procedures

James R. Swisher · Paul Hyden · Sheldon H. Jacobson · Lee W. Schruben

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Simulation Techniques and Applications Simulation and Modeling Applications Complex Systems and Decision Making

Abstract

Discrete event simulation optimization is a problem of significant interest to practitioners interested in extracting useful information about an actual (or yet to be designed) system that can be modeled using discrete event simulation. This paper presents a brief survey of the literature on discrete event simulation optimization over the past decade (1988 to the present). Swisher et al. (2000) provides a more comprehensive review of this topic while Jacobson and Schruben (1989) covers the literature preceding 1988. Optimization of both discrete and continuous input parameters are examined. The continuous input parameter case is separated into gradient and non-gradient based optimization procedures. The discrete input parameter case differentiates techniques appropriate for small and for large numbers of feasible input parameter values.

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References

1951A Stochastic Approximation Method 1992Multivariate stochastic approximation using a simultaneous perturbation gradient approximation 1952Stochastic Estimation of the Maximum of a Regression Function 1991Gradient Estimation via Perturbation Analysis 1997Optimization of computer simulation models with rare events 1996Design and Analysis of Experiments for Statistical Selection, Screening and Multiple Comparisons 1992Ordinal optimization of DEDS 1994Optimization via simulation: A review

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