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Guided Local Search

  • Chapter
Handbook of Metaheuristics

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 57))

Abstract

The combinatorial explosion problem prevents complete algorithms from solving many real-life combinatorial optimization problems. In many situations, heuristic search methods are needed. This chapter describes the principles of Guided Local Search (GLS) and Fast Local Search (FLS) and surveys their applications. GLS is a penalty-based meta-heuristic algorithm that sits on top of other local search algorithms, with the aim to improve their efficiency and robustness. FLS is a way of reducing the size of the neighborhood so as to improve the efficiency of local search. The chapter also provides guidance for implementing and using GLS and FLS. Four problems, representative of general application categories, are examined with detailed information provided on how to build a GLS-based method in each case.

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Author information

Authors and Affiliations

  1. Research Department, BTexact Technologies, Marthlesham Heath, BTplc, Orion Building, mlb1/pp12, Ipswich, IP5 3RE, UK

    Christos Voudouris

  2. Department of Computer Science, Univeristy of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK

    Edward P. K. Tsang

Authors
  1. Christos Voudouris
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  2. Edward P. K. Tsang
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Editors and Affiliations

  1. Leeds School of Business, University of Colorado at Boulder, USA

    Fred Glover

  2. College of Business, University of Colorado at Denver, USA

    Gary A. Kochenberger

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© 2003 Kluwer Academic Publishers

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Voudouris, C., Tsang, E.P.K. (2003). Guided Local Search. In: Glover, F., Kochenberger, G.A. (eds) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol 57. Springer, Boston, MA. https://doi.org/10.1007/0-306-48056-5_7

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  • DOI: https://doi.org/10.1007/0-306-48056-5_7

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-7263-5

  • Online ISBN: 978-0-306-48056-0

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