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Iterated Local Search

In: Handbook of Heuristics

Author

Listed:
  • Thomas Stützle

    (Université Libre de Bruxelles (ULB), IRIDIA)

  • Rubén Ruiz

    (Universitat Politécnica de València
    Amazon.com, Inc., AMAZON)

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 of 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.

Suggested Citation

  • Thomas Stützle & Rubén Ruiz, 2025. "Iterated Local Search," Springer Books, in: Rafael Martí & Panos M. Pardalos & Mauricio G.C. Resende (ed.), Handbook of Heuristics, edition 0, chapter 26, pages 779-807, Springer.
    • Handle: RePEc:spr:sprchp:978-3-032-00385-0_8
    DOI: 10.1007/978-3-032-00385-0_8
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