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Improved Memetic Algorithm for Solving the Minimum Weight Vertex Independent Dominating Set

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  • Yupeng Zhou

    (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
    School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China)

  • Jinshu Li

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

  • Yang Liu

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

  • Shuai Lv

    (Urban Construction Archives, Changchun 130000, China)

  • Yong Lai

    (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
    College of Computer Science and Technology, Jilin University, Changchun 130012, China)

  • Jianan Wang

    (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
    School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China)

Abstract

The minimum weight vertex independent dominating set (MWVIDS) problem is an important version of the minimum independent dominating set. The MWVIDS problem has a number of applications in many fields. However, the MWVIDS problem is known to be NP-hard and thus computationally challenging. In this work, we present the improved memetic algorithm called MSSAS for solving the MWVIDS problem. The proposed MSSAS algorithm combines probability-based dynamic optimization (PDO) (to generate good and diverse offspring solutions by assembling elements of existing good solutions) as well as a local search phase named C_LS (to seek high-quality local optima by combining the idea of constrained-based two-level configuration checking strategy and tabu mechanism). The extensive results on popular DIMACS and BHOLIB benchmarks demonstrate that MSSAS competes favorably with the state-of-the-art algorithms. In addition, we analyze the benefits of the newly raised components including two above proposed ideas with our memetic framework. It is worth mentioning that the combination of both components has excellent effects for the MWVIDS problem.

Suggested Citation

  • Yupeng Zhou & Jinshu Li & Yang Liu & Shuai Lv & Yong Lai & Jianan Wang, 2020. "Improved Memetic Algorithm for Solving the Minimum Weight Vertex Independent Dominating Set," Mathematics, MDPI, vol. 8(7), pages 1-17, July.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:7:p:1155-:d:384597
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    References listed on IDEAS

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    Cited by:

    1. Alejandro Lara-Caballero & Diego González-Moreno, 2023. "A Population-Based Local Search Algorithm for the Identifying Code Problem," Mathematics, MDPI, vol. 11(20), pages 1-17, October.

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