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Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems

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  • Xinbo Zhang
  • Feng Zhang
  • Xiaohong Chen
  • Zhong Wan

Abstract

A polymorphic uncertain linear programming (PULP) model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.

Suggested Citation

  • Xinbo Zhang & Feng Zhang & Xiaohong Chen & Zhong Wan, 2014. "Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems," Journal of Optimization, Hindawi, vol. 2014, pages 1-10, February.
  • Handle: RePEc:hin:jjopti:896756
    DOI: 10.1155/2014/896756
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    References listed on IDEAS

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    1. S. P. Sethi & H. Yan & H. Zhang & Q. Zhang, 2002. "Optimal and Hierarchical Controls in Dynamic Stochastic Manufacturing Systems: A Survey," Manufacturing & Service Operations Management, INFORMS, vol. 4(2), pages 133-170.
    2. Mula, Josefa & Peidro, David & Poler, Raul, 2010. "The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand," International Journal of Production Economics, Elsevier, vol. 128(1), pages 136-143, November.
    3. Mula, J. & Poler, R. & Garcia-Sabater, J.P. & Lario, F.C., 2006. "Models for production planning under uncertainty: A review," International Journal of Production Economics, Elsevier, vol. 103(1), pages 271-285, September.
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