Guided Local Search

Christos Voudouris (), Edward P.K. Tsang () and Abdullah Alsheddy ()
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Christos Voudouris: Group Chief Technology Office, BT plc, Orion Building, mlb1/pp12, Marthlesham Heath
Edward P.K. Tsang: University of Essex
Abdullah Alsheddy: University of Essex

Chapter Chapter 11 in Handbook of Metaheuristics, 2010, pp 321-361 from Springer

Abstract: 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.

Keywords: Guided Local Search (GLS); Fast Local Search (FLS); Radio Link Frequency Assignment Problem (RLFAP); Augmented Objective Function; Vehicle Routing Problem (VRP) (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1007/978-1-4419-1665-5_11

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