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Iterated k-Opt Local Search for the Maximum Clique Problem

  • Kengo Katayama
  • Masashi Sadamatsu
  • Hiroyuki Narihisa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Local Search Travel Salesman Problem Travel Salesman Problem Memetic Algorithm Iterate Local Search 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Kengo Katayama
    • 1
  • Masashi Sadamatsu
    • 1
  • Hiroyuki Narihisa
    • 1
  1. 1.Information and Computer Engineering, Okayama University of Science 1 - 1 Ridai-cho, Okayama, 700-0005Japan

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