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NILS: A Neutrality-Based Iterated Local Search and Its Application to Flowshop Scheduling

  • Marie-Eléonore Marmion
  • Clarisse Dhaenens
  • Laetitia Jourdan
  • Arnaud Liefooghe
  • Sébastien Verel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6622)

Abstract

This paper presents a new methodology that exploits specific characteristics from the fitness landscape. In particular, we are interested in the property of neutrality, that deals with the fact that the same fitness value is assigned to numerous solutions from the search space. Many combinatorial optimization problems share this property, that is generally very inhibiting for local search algorithms. A neutrality-based iterated local search, that allows neutral walks to move on the plateaus, is proposed and experimented on a permutation flowshop scheduling problem with the aim of minimizing the makespan. Our experiments show that the proposed approach is able to find improving solutions compared with a classical iterated local search. Moreover, the tradeoff between the exploitation of neutrality and the exploration of new parts of the search space is deeply analyzed.

Keywords

Search Space Schedule Problem Local Search Local Search Algorithm Neutral Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marie-Eléonore Marmion
    • 1
    • 2
  • Clarisse Dhaenens
    • 1
    • 2
  • Laetitia Jourdan
    • 2
  • Arnaud Liefooghe
    • 1
    • 2
  • Sébastien Verel
    • 2
    • 3
  1. 1.LIFL – CNRSUniversité Lille 1France
  2. 2.INRIA Lille-Nord EuropeFrance
  3. 3.CNRSUniversity of Nice Sophia AntipolisFrance

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