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Type 2 Fully Fuzzy Linear Programming

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  • Mohamed El Alaoui

    (ENSAM, Université Moulay Ismaïl, Morocco)

Abstract

Since its inception, fuzzy linear programming (FLP) has proved to be a more powerful tool than classical linear programming to optimize real-life problems dealing with uncertainty. However, the proposed models are partially fuzzy; in other words, they suppose that only some aspects can be uncertain, while others have to be crisp. Furthermore, the few methods that deal with fully fuzzy problems use Type 1 fuzzy membership function, while Type 2 fuzzy logic captures the uncertainty in a more suitable way. This work presents a fully fuzzy linear programming approach in which all parameters are represented by unrestricted Interval Type 2 fuzzy numbers (IT2FN) and variables by positive IT2FN. The treated comparative results show that the proposed achieves a better optimized function while permitting consideration of both equality and inequality constraints.

Suggested Citation

  • Mohamed El Alaoui, 2021. "Type 2 Fully Fuzzy Linear Programming," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 10(4), pages 37-56, October.
    • Handle: RePEc:igg:jfsa00:v:10:y:2021:i:4:p:37-56
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