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Handbook of Metaheuristics pp 321–361Cite as

Guided Local Search

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 146))

Abstract

Combinatorial explosion is a well-known phenomenon that 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 metaheuristic 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 neighbourhood 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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Notes

  1. 1.

    To evaluate the change in the cost function (11.13) caused by a move normally requires \(O(n)\) time. Since there are \(O(n^2)\) moves to be evaluated, the search of the neighbourhood without the update scheme requires \(O(n^3)\) time.

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  1. Group Chief Technology Office, BT plc, Orion Building, mlb1/pp12, Marthlesham Heath, Ipswich, IP5 3RE, UK

    Christos Voudouris

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

    Edward P.K. Tsang & Abdullah Alsheddy

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  1. Christos Voudouris
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  1. , Département de mathématiques et génie in, École Polytechnique Montréal, Montreal, H3C 3A7, Québec, Canada

    Michel Gendreau

  2. Dépt. Informatique et Recherche, Opérationnelle, Université de Montreal, Pavillon André-Aisenstadt, Montreal, H3C 3J7, Québec, Canada

    Jean-Yves Potvin

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Voudouris, C., Tsang, E.P., Alsheddy, A. (2010). Guided Local Search. In: Gendreau, M., Potvin, JY. (eds) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol 146. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1665-5_11

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