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Geometric Programming with Discrete Variables Subject to Max-Product Fuzzy Relation Constraints

Author

Listed:
  • Zejian Qin
  • Bingyuan Cao
  • Shu-Cherng Fang
  • Xiao-Peng Yang

Abstract

The problem of geometric programming subject to max-product fuzzy relation constraints with discrete variables is studied. The major difficulty in solving this problem comes from nonconvexity caused by these product terms in the general geometric function and the max-product relation constraints. We proposed a 0-1 mixed integer linear programming model and adopted the branch-and-bound scheme to solve the problem. Numerical experiments confirm that the proposed solution method is effective.

Suggested Citation

  • Zejian Qin & Bingyuan Cao & Shu-Cherng Fang & Xiao-Peng Yang, 2018. "Geometric Programming with Discrete Variables Subject to Max-Product Fuzzy Relation Constraints," Discrete Dynamics in Nature and Society, Hindawi, vol. 2018, pages 1-8, April.
    • Handle: RePEc:hin:jnddns:1610349
    DOI: 10.1155/2018/1610349
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    References listed on IDEAS

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    1. Han-Lin Li & Hao-Chun Lu, 2009. "Global Optimization for Generalized Geometric Programs with Mixed Free-Sign Variables," Operations Research, INFORMS, vol. 57(3), pages 701-713, June.
    2. Han-Lin Li & Yao-Huei Huang & Shu-Cherng Fang, 2013. "A Logarithmic Method for Reducing Binary Variables and Inequality Constraints in Solving Task Assignment Problems," INFORMS Journal on Computing, INFORMS, vol. 25(4), pages 643-653, November.
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