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Stochastic Local Search Algorithms: An Overview

  • Chapter
Book cover Springer Handbook of Computational Intelligence

Part of the book series: Springer Handbooks ((SHB))

Abstract

In this chapter, we give an overview of the main concepts underlying the stochastic local search (GlossaryTerm

SLS

) framework and outline some of the most relevant GlossaryTerm

SLS

techniques. We also discuss some major recent research directions in the area of stochastic local search. The remainder of this chapter is structured as follows. In Sect. 54.1, we situate the notion of GlossaryTerm

SLS

within the broader context of fundamental search paradigms and briefly review the definition of an GlossaryTerm

SLS

algorithm. In Sect. 54.2, we summarize the main issues and trends in the design of greedy constructive and iterative improvement algorithms, while in Sects. 54.3–54.5, we provide a concise overview of some of the most widely used simple, hybrid, and population-based GlossaryTerm

SLS

methods. Finally, in Sect. 54.6, we discuss some recent topics of interest, such as the systematic design of GlossaryTerm

SLS

algorithms and methods for the automatic configuration of GlossaryTerm

SLS

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Abbreviations

ACO:

ant colony optimization

DLS:

dynamic local search

EA:

evolutionary algorithm

GRASP:

greedy randomized adaptive search procedure

IG:

iterated greedy

ILS:

iterated local search

MA:

memetic algorithm

PbO:

programming by optimization

PII:

probabilistic iterative improvement

RII:

randomized iterative improvement

SA:

simulated annealing

SAT:

satisfiability

SLS:

stochastic local search

TSP:

traveling salesman problem

TS:

tabu search

VND:

variable neighborhood descent

VNS:

variable neighborhood search

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Authors and Affiliations

  1. Dep. Computer Science, University of British Columbia, 2366 Main Mall, BC V6T 1Z4, Vancouver, Canada

    Holger H. Hoos

  2. IIRIDIA, CP 194/6, Université libre de Bruxelles (ULB), Av. F. Roosevelt 50, 1050, Brussels, Belgium

    Thomas Stützle

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  1. Holger H. Hoos
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Correspondence to Holger H. Hoos .

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  1. Systems Research Inst., Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

  2. Dep. Electrical and Computer Engineering, University of Alberta, 116 Street 9107, T6J 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

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Hoos, H.H., Stützle, T. (2015). Stochastic Local Search Algorithms: An Overview. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_54

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