Iterated Greedy

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

Chapter 18 in Handbook of Heuristics, 2018, pp 547-577 from Springer

Abstract: Abstract Iterated greedy is a search method that iterates through applications of construction heuristics using the repeated execution of two main phases, the partial destruction of a complete candidate solution and a subsequent reconstruction of a complete candidate solution. Iterated greedy is based on a simple principle, and methods based on this principle have been proposed and published several times in the literature under different names such as simulated annealing, iterative flattening, ruin-and-recreate, large neighborhood search, and others. Despite its simplicity, iterated greedy has led to rather high-performing algorithms. In combination with other heuristic optimization techniques such as a local search, it has given place to state-of-the-art algorithms for various problems. This paper reviews the main principles of iterated greedy algorithms, relates the basic technique to the various proposals based on this principle, discusses its relationship with other optimization techniques, and gives an overview of problems to which iterated greedy has been successfully applied.

Keywords: Stochastic local search; Metaheuristics; Iterated greedy; Greedy methods; Local search; Constructive search (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-07124-4_10

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DOI: 10.1007/978-3-319-07124-4_10

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