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On optimality and duality theorems of nonlinear disjunctive fractional minmax programs

机译:非线性析分分数minmax程序的最优性和对偶定理。

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This paper is concerned with the study of optimality conditions for disjunctive fractional minmax programming problems in which the decision set can be considered as a union of a family of convex sets. Dinkelbach's global optimization approach for finding the global maximum of the fractional programming problem is discussed. Using the Lagrangian function definition for this type of problem, the Kuhn-Tucker saddle point and stationary-point problems are established. In addition, via the concepts of Mond-Weir type duality and Schaible type duality, a general dual problem is formulated and some weak, strong and converse duality theorems are proven. (c) 2006 Elsevier B.V. All rights reserved.
机译:本文关注于析取分数最小极大规划问题的最优条件的研究,其中决策集可以被视为凸集族的并集。讨论了Dinkelbach用于寻找分数规划问题的全局最大值的全局优化方法。使用针对此类问题的拉格朗日函数定义,建立了Kuhn-Tucker鞍点和固定点问题。此外,通过Mond-Weir型对偶和Schaible型对偶的概念,提出了一个一般对偶问题,并证明了一些弱,强和逆对偶定理。 (c)2006 Elsevier B.V.保留所有权利。

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