Simulation optimization: a review of algorithms and applications

Simulation optimization 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 mult...

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Veröffentlicht in:4OR Jg. 12; H. 4; S. 301 - 333
Hauptverfasser: Amaran, Satyajith, Sahinidis, Nikolaos V., Sharda, Bikram, Bury, Scott J.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2014
Springer Nature B.V
Schlagworte:
Algebra
Algorithms
Business and Management
Industrial and Production Engineering
Invited Survey
Mathematical functions
Mathematical programming
Operations research
Operations Research/Decision Theory
Optimization
R&D
Random variables
Research & development
Simulation
Software
90-02 Operations research, mathematical programming: Research exposition (monographs, survey articles)
90C56 Derivative-free methods and methods using generalized derivatives
Simulation optimization
Optimization via simulation
Derivative-free optimization
65-02 Numerical analysis: Research exposition (monographs, survey articles)
ISSN:1619-4500, 1614-2411
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Beschreibung
Zusammenfassung:Simulation optimization 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 simulation optimization 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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ISSN:1619-4500
1614-2411
DOI:10.1007/s10288-014-0275-2