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A Restart Diversification Strategy for Iterated Local Search to Maximum Clique Problem

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Book cover Complex, Intelligent, and Software Intensive Systems (CISIS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 772))

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Abstract

Iterated local search metaheuristic provides high quality solutions, in spite of a simple framework, for a large number of combinatorial optimization problems. However the search stagnation sometimes occur before finding a high quality solution for difficult problem instances particularly. One simple way to overcome such stagnation is to introduce a restart strategy into the framework that forcibly changes its search point. In this paper, we present a restart diversification strategy (RDS) for an iterated local search incorporating k-opt local search (KLS), called Iterated KLS (IKLS), for the maximum clique problem. For the RDS, we accumulate the information of solutions by KLS and it occasionally diversifies the main search of IKLS by moving to unexplored points based on the information. IKLS with the RDS is evaluated on DIMACS graphs. The experimental results showed that the RDS contributes to the improvement of the main search of IKLS for several difficult graphs.

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Notes

  1. 1.

    To perform effective searches of KLS with IKLS, two simple devices (see the Subsects. 3.1 and 3.2) have been given for the original KLS shown in [6]. Note that in the context of RDS, third device in KLS is described at the Sect. 4.

  2. 2.

    http://dimacs.rutgers.edu/Challenges/.

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Author information

Authors and Affiliations

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

    Kazuho Kanahara, Kengo Katayama, Takeshi Okano, Elis Kulla, Tetsuya Oda & Noritaka Nishihara

Authors
  1. Kazuho Kanahara
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  2. Kengo Katayama
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  3. Takeshi Okano
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  4. Elis Kulla
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  5. Tetsuya Oda
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  6. Noritaka Nishihara
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Corresponding author

Correspondence to Kengo Katayama .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology , Fukuoka, Japan

    Leonard Barolli

  2. Department of Computer Science, COMSATS Institute of Information Technology , Islamabad, Pakistan

    Nadeem Javaid

  3. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology , Fukuoka, Japan

    Makoto Ikeda

  4. Department of Advanced Sciences, Hosei University , Tokyo, Japan

    Makoto Takizawa

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Kanahara, K., Katayama, K., Okano, T., Kulla, E., Oda, T., Nishihara, N. (2019). A Restart Diversification Strategy for Iterated Local Search to Maximum Clique Problem. In: Barolli, L., Javaid, N., Ikeda, M., Takizawa, M. (eds) Complex, Intelligent, and Software Intensive Systems. CISIS 2018. Advances in Intelligent Systems and Computing, vol 772. Springer, Cham. https://doi.org/10.1007/978-3-319-93659-8_61

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