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A Global Optimization Approach for Solving Generalized Nonlinear Multiplicative Programming Problem

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  • Lin-Peng Yang
  • Pei-Ping Shen
  • Yong-Gang Pei

Abstract

This paper presents a global optimization algorithm for solving globally the generalized nonlinear multiplicative programming (MP) with a nonconvex constraint set. The algorithm uses a branch and bound scheme based on an equivalently reverse convex programming problem. As a result, in the computation procedure the main work is solving a series of linear programs that do not grow in size from iterations to iterations. Further several key strategies are proposed to enhance solution production, and some of them can be used to solve a general reverse convex programming problem. Numerical results show that the computational efficiency is improved obviously by using these strategies.

Suggested Citation

  • Lin-Peng Yang & Pei-Ping Shen & Yong-Gang Pei, 2014. "A Global Optimization Approach for Solving Generalized Nonlinear Multiplicative Programming Problem," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-14, April.
    • Handle: RePEc:hin:jnlaaa:641909
    DOI: 10.1155/2014/641909
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    Cited by:

    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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