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Exact methods for multi-objective combinatorial optimisation

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Publication date15/05/2016
Host publicationMultiple criteria decision analysis: state of the art surveys
EditorsSalvatore Greco, Matthias Ehrgott, Jose Rui Figueira
Place of PublicationNew York
PublisherSpringer
Pages817-850
Number of pages34
Edition2nd
ISBN (electronic)9781493930944
ISBN (print)9781493930937
<mark>Original language</mark>English

Publication series

NameInternational Series in Operations Research and Management Science
PublisherSpringer
Volume233
ISSN (Print)0884-8289

Abstract

In this chapter we consider multi-objective optimisation problems with a combinatorial structure. Such problems have a discrete feasible set and can be formulated as integer (usually binary) optimisation problems with multiple (integer valued) objectives. We focus on a review of exact methods to solve such problems. First, we provide definitions of the most important classes of solutions and explore properties of such problems and their solution sets. Then we discuss the most common approaches to solve multi-objective combinatorial optimisation problems. These approaches include extensions of single objective algorithms, scalarisation methods, the two-phase method and multi-objective branch and bound. For each of the approaches we provide references to specific algorithms found in the literature. We end the chapter with a description of some other algorithmic approaches for MOCO problems and conclusions suggesting directions for future research.