Duality theorem of nondifferentiable convex multiobjective programming
Necessary and sufficient conditions of Fritz John type for Pareto optimality of multiobjective programming problems are derived. This article suggests to establish a Wolfe-type duality theorem for nonlinear, nondifferentiable, convex multiobjective minimization problems. The vector Lagrangian and the generalized saddle point for Pareto optimality are studied. Some previously known results are shown to be special cases of the results described in this paper.
Key WordsMultiobjective programming Pareto optimality dual problems of multiobjective programming weak Pareto optimality generalized saddle points
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