Document Open Access Logo

PACE Solver Description: Weighting-Based Local Search Heuristic for the Hitting Set Problem

Authors Canhui Luo , Qingyun Zhang , Zhouxing Su , Zhipeng Lü

PDF

File

Thumbnail PDF
PDF
LIPIcs.IPEC.2025.40.pdf
  • Filesize: 0.53 MB
  • 4 pages

Document Identifiers

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Combinatorial optimization
  • Computing methodologies → Search methodologies
Keywords
  • PACE 2025
  • Dominating Set
  • Hitting Set
  • Heuristic Optimization
  • Weighted Local Search

Metrics

Abstract

We present a unified heuristic solver for the PACE 2025 challenge, addressing both the dominating set and hitting set problems by reducing them to the unicost set covering problem. Our solver applies standard reduction rules, a multi-round frequency-based greedy initializer, and a local search guided by adaptive element weights. Additional techniques, such as component-level exact solving and swap restriction, further enhance performance. In the final official evaluation, our proposed solver achieved second place in the heuristic track for the dominating set problem of the PACE 2025 challenge, while securing first place in the heuristic track for the hitting set problem.

Cite As Get BibTex

Canhui Luo, Qingyun Zhang, Zhouxing Su, and Zhipeng Lü. PACE Solver Description: Weighting-Based Local Search Heuristic for the Hitting Set Problem. In 20th International Symposium on Parameterized and Exact Computation (IPEC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 358, pp. 40:1-40:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.IPEC.2025.40

Author Details

Canhui Luo
  • Huazhong University of Science and Technology, Wuhan, China
Qingyun Zhang
  • Huazhong University of Science and Technology, Wuhan, China
Zhouxing Su
  • Huazhong University of Science and Technology, Wuhan, China
Zhipeng Lü
  • Huazhong University of Science and Technology, Wuhan, China

Funding

This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 62402191, the Interdisciplinary Research Program of Hust under Grant 5003300129, and Innovation Program for Quantum Science and Technology under Grant No. 2024ZD0300500.

Acknowledgements

We want to thank the organizers of PACE 2025 challenge and all other participants for creating such an engaging challenge.

Supplementary Materials

References

  1. Fred Glover. Future paths for integer programming and links to artificial intelligence. Computers & operations research, 13(5):533-549, 1986. URL: https://doi.org/10.1016/0305-0548(86)90048-1.
  2. Canhui Luo. lxily/PACE2025.DS-HS. Software, (visited on 2025-12-03). URL: https://github.com/lxily/PACE2025.DS-HS
    Software Heritage Logo archived version
    full metadata available at: https://doi.org/10.4230/artifacts.25227
  3. Zhouxing Su, Qingyun Zhang, Zhipeng Lü, Chu-Min Li, Weibo Lin, and Fuda Ma. Weighting-based variable neighborhood search for optimal camera placement. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 35, pages 12400-12408, 2021. URL: https://doi.org/10.1609/AAAI.V35I14.17471.
  4. Qingyun Zhang, Zhipeng Lü, Zhouxing Su, and Chumin Li. A vertex weighting-based double-tabu search algorithm for the classical p-center problem. Computers & Operations Research, 160:106373, 2023. URL: https://doi.org/10.1016/J.COR.2023.106373.
  5. Qingyun Zhang, Zhipeng Lü, Zhouxing Su, Chumin Li, Yuan Fang, and Fuda Ma. Vertex weighting-based tabu search for p-center problem. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence, pages 1481-1487, 2021. Google Scholar
Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact