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Iterated k-Opt Local Search for the Maximum Clique Problem

  • Conference paper
Evolutionary Computation in Combinatorial Optimization (EvoCOP 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4446))

Abstract

This paper presents a simple iterated local search metaheuristic incorporating a k-opt local search (KLS), called Iterated KLS (IKLS for short), for solving the maximum clique problem (MCP). IKLS consists of three components: LocalSearch at which KLS is used, a Kick called LEC-Kick that escapes from local optima, and Restart that occasionally diversifies the search by moving to other points in the search space. IKLS is evaluated on DIMACS benchmark graphs. The results showed that IKLS is an effective algorithm for the MCP through comparisons with multi-start KLS and state-of-the-art metaheuristics.

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Authors and Affiliations

  1. Information and Computer Engineering, Okayama University of Science 1 - 1 Ridai-cho, Okayama, 700-0005, Japan

    Kengo Katayama, Masashi Sadamatsu & Hiroyuki Narihisa

Authors
  1. Kengo Katayama
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  2. Masashi Sadamatsu
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  3. Hiroyuki Narihisa
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Editor information

Carlos Cotta Jano van Hemert

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Katayama, K., Sadamatsu, M., Narihisa, H. (2007). Iterated k-Opt Local Search for the Maximum Clique Problem. In: Cotta, C., van Hemert, J. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2007. Lecture Notes in Computer Science, vol 4446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71615-0_8

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  • DOI: https://doi.org/10.1007/978-3-540-71615-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71614-3

  • Online ISBN: 978-3-540-71615-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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