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Solving Clique Partitioning Problems: A Comparison of Models and Commercial Solvers

Author

Listed:
  • Yu Du

    (University of Colorado at Denver, USA)

  • Gary Kochenberger

    (University of Colorado at Denver, USA)

  • Fred Glover

    (��University of Colorado at Boulder, USA)

  • Haibo Wang

    (��Texas A&M International University, USA)

  • Mark Lewis

    (�Missouri State University, USA)

  • Weihong Xie

    (�Guangdong University of Technology, P. R. China)

  • Takeshi Tsuyuguchi

    (��Texas A&M International University, USA)

Abstract

Finding good solutions to clique partitioning problems remains a computational challenge. With rare exceptions, finding optimal solutions for all but small instances is not practically possible. However, choosing the most appropriate modeling structure can have a huge impact on what is practical to obtain from exact solvers within a reasonable amount of run time. Commercial solvers have improved tremendously in recent years and the combination of the right solver and the right model can significantly increase our ability to compute acceptable solutions to modest-sized problems with solvers like CPLEX, GUROBI and XPRESS. In this paper, we explore and compare the use of three commercial solvers on modest sized test problems for clique partitioning. For each problem instance, a conventional linear model from the literature and a relatively new quadratic model are compared. Extensive computational experience indicates that the quadratic model outperforms the classic linear model as problem size grows.

Suggested Citation

  • Yu Du & Gary Kochenberger & Fred Glover & Haibo Wang & Mark Lewis & Weihong Xie & Takeshi Tsuyuguchi, 2022. "Solving Clique Partitioning Problems: A Comparison of Models and Commercial Solvers," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 59-81, January.
  • Handle: RePEc:wsi:ijitdm:v:21:y:2022:i:01:n:s0219622021500504
    DOI: 10.1142/S0219622021500504
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    Cited by:

    1. Jovanovic, Raka & Sanfilippo, Antonio P. & Voß, Stefan, 2023. "Fixed set search applied to the clique partitioning problem," European Journal of Operational Research, Elsevier, vol. 309(1), pages 65-81.

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