國立僑生大學先修班學報
Permanent URI for this collectionhttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/217
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Item Mixed Type Duality For Multiobjective Fractional Programming Involving Nonsmooth (F, p)-convex Functions(國立僑生大學先修班, 2003-12-??) J. C. LiuWe restate the necessary optimality conditions of Rcf. 1 to formulate one mixed type dual model for multiobjective fractional programming problems with nonsmooth (F, p)-convex functions. This mixed type dual model unifies Wolfe type dual model and Mond-Weir type dual model. We also establish weak, strong and converse duality theorems.Item Sufficiency Criteria And Duality For Complex Nondifferentiable Fractional Programming Involving Pseudoinvex Function(國立僑生大學先修班, 1998-07-??) 劉正傳; 林世昌; J. C. Liu; S. C. LinUnder different forms of invexity conditions, sufficient conditions and five duality models are presented for the nondifferentiable fractional programming problem containing square roots of positive semidefinite Hermitian quadratic forms.Item Duality For Multiobjective Fractional Programming Involving Nonsmooth (F,p)-convex Functions(國立僑生大學先修班, 1996-07-??) 劉正傳; J. C. LiuWolfe type dual for multiobjective fractional programming problem is introduced and certain duality results have been derived in the framework of (F, p)-convex functions.Item Optimality and Duality For Generalized Fractional Programming Involving Nonsmooth Pseudoinvex Functions(國立僑生大學先修班, 1995-07-??) 劉正傳; J. C. LiuUsing a parametric approach,we establish necessary and sufficient conditions and derive duality theorems for a class of nonsmooth generalized minimax fractional programming problems containing pseudo-invex functions.Item Duality For NonditTerentiable Multiobjective Programming Without A Constraint Qualification(國立僑生大學先修班, 1993-07-??) 劉正傳; J. C. LiuNecessary and sufficient conditions without constraint qualification for pareto optimality of multiobjective programming are derived. This article suggests the establishment of a Wolfe-type duality theorem for nondifferentiable, convex, multiobjective minimization problems. The vector Lagrangian and the generalized saddle point for pareto optimality are studied. Key works. Multiobjective programming, pareto optimality, cone of directions, vector Lagrangian, Pareto saddle point.