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Duality theorems and saddle point optimality conditions in fuzzy nonlinear programming problems based on different solution concepts

机译:基于不同解概念的模糊非线性规划问题的对偶定理和鞍点最优条件

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摘要

Under a general setting of partial ordering defined on the set of all fuzzy numbers, the duality theorems and saddle point optimality conditions in fuzzy nonlinear programming problems based on two solution concepts for primal problem and three solution concepts for dual problem are derived in this paper. Those solution concepts are inspired by the nondominated solution concept employed in multiobjective programming problems, since the ordering among fuzzy numbers introduced in this paper is a partial ordering, not a total ordering. We also provide a concept of fuzzy scalar (inner) product for fuzzy numbers. Then the fuzzy-valued Lagrangian function and the fuzzy-valued Lagrangian dual function are proposed via the concept of fuzzy scalar product. Under these settings, the dual problem is formulated, and the objective function of this dual problem is a point-to-set fuzzy-valued function. In this case, three solution concepts for dual problem are proposed. The duality theorems and saddle point optimality conditions can be naturally elicited based on these three solution concepts.
机译:在所有模糊数的集合上定义了偏序的一般设置下,导出了基于两个原始问题解和三个对偶问题解的模糊非线性规划问题的对偶定理和鞍点最优性条件。这些解决方案概念受到多目标编程问题中采用的非主导解决方案概念的启发,因为本文介绍的模糊数之间的排序是部分排序,而不是总排序。我们还提供了模糊数的模糊标量(内)积的概念。然后通过模糊标量积的概念,提出了模糊值拉格朗日函数和模糊值拉格朗日对偶函数。在这些设置下,制定了对偶问题,并且该对偶问题的目标函数是点对集模糊值函数。在这种情况下,提出了双重问题的三个解决方案概念。根据这三个解的概念,自然可以得出对偶定理和鞍点最优条件。

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