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Phased local search for the maximum clique problem

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  • Wayne Pullan

    (Griffith University)

Abstract

This paper introduces Phased Local Search (PLS), a new stochastic reactive dynamic local search algorithm for the maximum clique problem. (PLS) interleaves sub-algorithms which alternate between sequences of iterative improvement, during which suitable vertices are added to the current clique, and plateau search, where vertices of the current clique are swapped with vertices not contained in the current clique. The sub-algorithms differ in their vertex selection techniques in that selection can be solely based on randomly selecting a vertex, randomly selecting within highest vertex degree or randomly selecting within vertex penalties that are dynamically adjusted during the search. In addition, the perturbation mechanism used to overcome search stagnation differs between the sub-algorithms. (PLS) has no problem instance dependent parameters and achieves state-of-the-art performance for the maximum clique problem over a large range of the commonly used DIMACS benchmark instances.

Suggested Citation

  • Wayne Pullan, 2006. "Phased local search for the maximum clique problem," Journal of Combinatorial Optimization, Springer, vol. 12(3), pages 303-323, November.
    • Handle: RePEc:spr:jcomop:v:12:y:2006:i:3:d:10.1007_s10878-006-9635-y
    DOI: 10.1007/s10878-006-9635-y
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    Citations

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    Cited by:

    1. Wu, Qinghua & Hao, Jin-Kao, 2015. "A review on algorithms for maximum clique problems," European Journal of Operational Research, Elsevier, vol. 242(3), pages 693-709.
    2. Seyedmohammadhossein Hosseinian & Dalila B. M. M. Fontes & Sergiy Butenko, 2020. "A Lagrangian Bound on the Clique Number and an Exact Algorithm for the Maximum Edge Weight Clique Problem," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 747-762, July.
    3. Qinghua Wu & Jin-Kao Hao, 2013. "An adaptive multistart tabu search approach to solve the maximum clique problem," Journal of Combinatorial Optimization, Springer, vol. 26(1), pages 86-108, July.
    4. 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.
    5. Zhiqiang Zhang & Zhongwen Li & Xiaobing Qiao & Weijun Wang, 2019. "An Efficient Memetic Algorithm for the Minimum Load Coloring Problem," Mathematics, MDPI, vol. 7(5), pages 1-20, May.
    6. Assif Assad & Kusum Deep, 2018. "A heuristic based harmony search algorithm for maximum clique problem," OPSEARCH, Springer;Operational Research Society of India, vol. 55(2), pages 411-433, June.

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