Iterated Local Search

  • Stützle T
  • Ruiz R
N/ACitations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Stützle, T., & Ruiz, R. (2017). Iterated Local Search. In Handbook of Heuristics (pp. 1–27). Springer International Publishing. https://doi.org/10.1007/978-3-319-07153-4_8-1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free