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Optimization via simulation: A review. (English) Zbl 0833.90089
Summary: We review techniques for optimizing stochastic discrete-event systems via simulation. We discuss both the discrete parameter case and the continuous parameter case, but concentrate on the latter which has dominated most of the recent research in the area. For the distance parameter case, we focus on the techniques for optimization from a finite set: multiple-comparison procedures and ranking-and-selection procedures. For the continuous parameter case, we focus on gradient-based methods, including perturbation analysis, the likelihood ratio method, and frequency domain experimentation. For illustrative purposes, we compare and contrast the implementation of the techniques for some simple discrete-event systems such as the \((s, S)\) inventory system and the \(GI/G/1\) queue.
Finally, we speculate on future directions for the field, particularly in the context of the rapid advances being made in parallel computing.

MSC:
90C15 Stochastic programming
90C31 Sensitivity, stability, parametric optimization
62J15 Paired and multiple comparisons; multiple testing
62F07 Statistical ranking and selection procedures
90-02 Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming
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