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Output-space branch-and-bound reduction algorithm for generalized linear fractional-multiplicative programming problem

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  • Gao, YueLin
  • Zhang, Bo

Abstract

In this paper, we investigate a class of linear fractional-multiplicative programs with exponents, which have important applications in finance and economy. By introducing p variables, the problem is re-represented as an equivalent problem. Immediately, two new linear relaxation strategies are proposed and embedded in the branch-and-bound framework, and the corresponding new global optimization algorithms are developed in combination with an acceleration technique. Furthermore, the theoretical convergence and computational complexity of the algorithms are elucidated. Numerical experiment results illustrate that both algorithms are effective and feasible.

Suggested Citation

  • Gao, YueLin & Zhang, Bo, 2023. "Output-space branch-and-bound reduction algorithm for generalized linear fractional-multiplicative programming problem," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p1:s0960077923008251
    DOI: 10.1016/j.chaos.2023.113924
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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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    7. H. P. Benson & G. M. Boger, 1997. "Multiplicative Programming Problems: Analysis and Efficient Point Search Heuristic," Journal of Optimization Theory and Applications, Springer, vol. 94(2), pages 487-510, August.
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    Cited by:

    1. Huang, Bingdi & Shen, Peiping, 2024. "An efficient branch and bound reduction algorithm for globally solving linear fractional programming problems," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).

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