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An effective population-based approach for the partial set covering problem

Author

Listed:
  • Ye Zhang

    (Northeast Normal University)

  • Jinlong He

    (Northeast Normal University)

  • Yupeng Zhou

    (Northeast Normal University)

  • Shuli Hu

    (Northeast Normal University)

  • Dunbo Cai

    (China Mobile (Suzhou) Software Technology Company Ltd.)

  • Naiyu Tian

    (Nanjing Research Institute of Electronic Engineering)

  • Minghao Yin

    (Northeast Normal University)

Abstract

The partial set covering problem (PSCP) is a significant combinatorial optimization problem that finds applications in numerous real-world scenarios. The objective of PSCP is to encompass a minimum number of subsets while ensuring the coverage of at least n elements. Due to its NP-hard nature, solving large-scale PSCP efficiently remains a critical issue in computational intelligence. To effectively tackle this challenge, we delve into a population-based approach that incorporates a modified tabu search, thereby striking a delicate balance between exploration and exploitation. To further enhance its efficacy, we employ the multiple path-relinking strategy and the fix-and-optimize process. Finally, the dynamic resource allocation scheme is utilized to save computing efforts. Comparative experiments of the proposed algorithm were conducted against three state-of-the-art competitors, across two distinct categories, encompassing 150 instances. The results significantly underscore the profound effectiveness of our proposed algorithm, as evidenced by the updating of 67 best-known solutions. Moreover, we conduct an in-depth analysis of the key components inherent to the algorithm, shedding light on their respective influences on the whole performance.

Suggested Citation

  • Ye Zhang & Jinlong He & Yupeng Zhou & Shuli Hu & Dunbo Cai & Naiyu Tian & Minghao Yin, 2025. "An effective population-based approach for the partial set covering problem," Journal of Heuristics, Springer, vol. 31(1), pages 1-32, March.
  • Handle: RePEc:spr:joheur:v:31:y:2025:i:1:d:10.1007_s10732-025-09552-7
    DOI: 10.1007/s10732-025-09552-7
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    References listed on IDEAS

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    1. Wang, Yiyuan & Pan, Shiwei & Al-Shihabi, Sameh & Zhou, Junping & Yang, Nan & Yin, Minghao, 2021. "An improved configuration checking-based algorithm for the unicost set covering problem," European Journal of Operational Research, Elsevier, vol. 294(2), pages 476-491.
    2. Masoud Yaghini & Mohammad Karimi & Mohadeseh Rahbar, 2015. "A set covering approach for multi-depot train driver scheduling," Journal of Combinatorial Optimization, Springer, vol. 29(3), pages 636-654, April.
    3. Gao, Chao & Yao, Xin & Weise, Thomas & Li, Jinlong, 2015. "An efficient local search heuristic with row weighting for the unicost set covering problem," European Journal of Operational Research, Elsevier, vol. 246(3), pages 750-761.
    4. López-Ibáñez, Manuel & Dubois-Lacoste, Jérémie & Pérez Cáceres, Leslie & Birattari, Mauro & Stützle, Thomas, 2016. "The irace package: Iterated racing for automatic algorithm configuration," Operations Research Perspectives, Elsevier, vol. 3(C), pages 43-58.
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