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A Restart Local Search for Solving Diversified Top- k Weight Clique Search Problem

Author

Listed:
  • Jun Wu

    (Information Science and Technology, Northeast Normal University, Changchun 130117, China)

  • Minghao Yin

    (Information Science and Technology, Northeast Normal University, Changchun 130117, China)

Abstract

Diversified top- k weight clique (DTKWC) search problem is an important generalization of the diversified top- k clique (DTKC) search problem with practical applications. The diversified top- k weight clique search problem aims to search k maximal cliques that can cover the maximum weight in a vertex weighted graph. In this work, we propose a novel local search algorithm called TOPKWCLQ for the DTKWC search problem which mainly includes two strategies. First, a restart strategy is adopted, which repeated the construction and updating processes of the maximal weight clique set. Second, a scoring heuristic is designed by giving different priorities for maximal weight cliques in candidate set. Meanwhile, a constraint model of the DTKWC search problem is constructed such that the research concerns can be evaluated. Experimental results show that the proposed algorithm TOPKWCLQ outperforms than the comparison algorithm on large-scale real-world graphs.

Suggested Citation

  • Jun Wu & Minghao Yin, 2021. "A Restart Local Search for Solving Diversified Top- k Weight Clique Search Problem," Mathematics, MDPI, vol. 9(21), pages 1-17, October.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:21:p:2674-:d:662009
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    References listed on IDEAS

    as
    1. Li, Chu-Min & Liu, Yanli & Jiang, Hua & Manyà, Felip & Li, Yu, 2018. "A new upper bound for the maximum weight clique problem," European Journal of Operational Research, Elsevier, vol. 270(1), pages 66-77.
    2. Yi Chu & Boxiao Liu & Shaowei Cai & Chuan Luo & Haihang You, 2020. "An efficient local search algorithm for solving maximum edge weight clique problem in large graphs," Journal of Combinatorial Optimization, Springer, vol. 39(4), pages 933-954, May.
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