Simulation optimization: a review of algorithms and applications

Simulation optimization: a review of algorithms and applications

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Article ID: iaor20162272
Volume: 240
Issue: 1
Start Page Number: 351
End Page Number: 380
Publication Date: May 2016
Journal: Annals of Operations Research
Authors: , , ,
Keywords: simulation, stochastic processes, decision, programming: mathematical
Abstract:

Simulation optimization (SO) refers to the optimization of an objective function subject to constraints, both of which can be evaluated through a stochastic simulation. To address specific features of a particular simulation–discrete or continuous decisions, expensive or cheap simulations, single or multiple outputs, homogeneous or heterogeneous noise–various algorithms have been proposed in the literature. As one can imagine, there exist several competing algorithms for each of these classes of problems. This document emphasizes the difficulties in SO as compared to algebraic model‐based mathematical programming, makes reference to state‐of‐the‐art algorithms in the field, examines and contrasts the different approaches used, reviews some of the diverse applications that have been tackled by these methods, and speculates on future directions in the field.

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