Discrete optimization via simulation

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)12_Chapter in an edited book (Author)Not applicablepeer-review

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Detail(s)

Original languageEnglish
Title of host publicationInternational Series in Operations Research and Management Science
EditorsMichael C. Fu
Place of PublicationNew York, NY
PublisherSpringer New York LLC
Pages9-44
Volume216
ISBN (Electronic)9781493913848
ISBN (Print)9781493913831
StatePublished - 2015

Publication series

NameInternational Series in Operations Research and Management Science
Volume216
ISSN (Print)0884-8289

Abstract

This chapter describes tools and techniques that are useful for optimization via simulation—maximizing or minimizing the expected value of a performance measure of a stochastic simulation—when the decision variables are discrete. Ranking and selection, globally and locally convergent random search and ordinal optimization are covered, along with a collection of “enhancements” that may be applied to many different discrete optimization via simulation algorithms. We also provide strategies for using commercial solvers.

Citation Format(s)

Discrete optimization via simulation. / HONG, Jeff; NELSON, B L; XU, J.

International Series in Operations Research and Management Science. ed. / Michael C. Fu. Vol. 216 New York, NY : Springer New York LLC, 2015. p. 9-44 2 (International Series in Operations Research and Management Science; Vol. 216).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)12_Chapter in an edited book (Author)Not applicablepeer-review