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Solving linear multiplicative programs via branch-and-bound: a computational experience

Author

Listed:
  • R. Cambini

    (Università di Pisa)

  • R. Riccardi

    (Università degli Studi di Brescia)

  • D. Scopelliti

    (Università degli Studi di Brescia)

Abstract

In this paper, linear multiplicative programs are approached with a branch-and-bound scheme and a detailed computational study is provided. Several underestimation functions are analyzed and various partitioning criteria are presented. A particular class of linear multiplicative programs, useful to solve some applicative bilevel problems, is considered from a theoretical point of view to emphasize an efficient solution method. Detailed results of the computational study are provided to point out the performances provided by using various underestimation functions and partitioning criteria, thus improving some of the results of the current literature.

Suggested Citation

  • R. Cambini & R. Riccardi & D. Scopelliti, 2023. "Solving linear multiplicative programs via branch-and-bound: a computational experience," Computational Management Science, Springer, vol. 20(1), pages 1-32, December.
    • Handle: RePEc:spr:comgts:v:20:y:2023:i:1:d:10.1007_s10287-023-00471-1
    DOI: 10.1007/s10287-023-00471-1
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    References listed on IDEAS

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    1. Peiping Shen & Kaimin Wang & Ting Lu, 2020. "Outer space branch and bound algorithm for solving linear multiplicative programming problems," Journal of Global Optimization, Springer, vol. 78(3), pages 453-482, November.
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    Cited by:

    1. Riccardo Cambini & Rossana Riccardi, 2024. "Optimality conditions for differentiable linearly constrained pseudoconvex programs," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 47(2), pages 497-512, December.

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