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Breakout local search for the cyclic cutwidth minimization problem

Author

Listed:
  • Mu He

    (Huazhong University of Science and Technology)

  • Qinghua Wu

    (Huazhong University of Science and Technology)

  • Yongliang Lu

    (Fuzhou University)

Abstract

The cyclic cutwidth minimization problem (CCMP) is a graph layout problem that involves embedding a graph onto a circle to minimize the maximum cutwidth of the graph. In this paper, we present breakout local search (BLS) for solving CCMP, which combines a dedicated local search procedure to discover high-quality local optimal solutions and an adaptive diversification strategy to escape from local optima. Extensive computational results on a wide set of 179 publicly available benchmark instances show that the proposed BLS algorithm has excellent performance with respect to the best-performing state-of-the-art approaches in terms of solution quality and computational time. In particular, it reports improved best-known solutions for 31 instances, while finding matching best-known results on 139 instances.

Suggested Citation

  • Mu He & Qinghua Wu & Yongliang Lu, 2022. "Breakout local search for the cyclic cutwidth minimization problem," Journal of Heuristics, Springer, vol. 28(5), pages 583-618, December.
    • Handle: RePEc:spr:joheur:v:28:y:2022:i:5:d:10.1007_s10732-022-09504-5
    DOI: 10.1007/s10732-022-09504-5
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    References listed on IDEAS

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    1. Pallavi Jain & Kamal Srivastava & Gur Saran, 2016. "Minimizing cyclic cutwidth of graphs using a memetic algorithm," Journal of Heuristics, Springer, vol. 22(6), pages 815-848, December.
    2. Fu, Zhang-Hua & Hao, Jin-Kao, 2014. "Breakout local search for the Steiner tree problem with revenue, budget and hop constraints," European Journal of Operational Research, Elsevier, vol. 232(1), pages 209-220.
    3. Benlic, Una & Epitropakis, Michael G. & Burke, Edmund K., 2017. "A hybrid breakout local search and reinforcement learning approach to the vertex separator problem," European Journal of Operational Research, Elsevier, vol. 261(3), pages 803-818.
    Full references (including those not matched with items on IDEAS)

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