Iterated Local Search

Thomas Stützle () and Rubén Ruiz ()
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Thomas Stützle: Université Libre de Bruxelles (ULB), IRIDIA
Rubén Ruiz: Universitat Politécnica de València, Grupo de Sistemas de Optimización Aplicada, Instituto Tecnológico de Informática, Ciudad Politécnica de la Innovación, Edificio 8G, Acc. B

Chapter 19 in Handbook of Heuristics, 2018, pp 579-605 from Springer

Abstract: Abstract Iterated local search is a metaheuristic that embeds an improvement heuristic within an iterative process generating a chain of solutions. Often, the improvement method is some kind of local search algorithm and, hence, the name of the metaheuristic. The iterative process in iterated local search consists in a perturbation of the current solution, leading to some intermediate solution that is used as a new starting solution for the improvement method. An additional acceptance criterion decides which of the solutions to keep for continuing this process. This simple idea has led to some very powerful algorithms that have been successfully used to tackle hard combinatorial optimization problems. In this chapter, we review the main ideas of iterated local search, exemplify its application to combinatorial problems, discuss historical aspects of the development of the method, and give an overview of some successful applications.

Keywords: Stochastic local search; Metaheuristics; Iterated local search; Local search; Perturbation; Acceptance criterion (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/978-3-319-07124-4_8

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