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Guided Local Search

  • Christos Voudouris
  • Edward P. K. Tsang
Part of the International Series in Operations Research & Management Science book series (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.

Keywords

Heuristic Search Meta-Heuristics Penalty-based Methods Guided Local Search Tabu Search Constraint Satisfaction 

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Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Christos Voudouris
    • 1
  • Edward P. K. Tsang
    • 2
  1. 1.Research Department, BTexact TechnologiesMarthlesham HeathIpswichUK
  2. 2.Department of Computer ScienceUniveristy of EssexColchesterUK

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