ε-Pareto optimality conditions for convex multiobjective programming via max function

被引:11
|
作者
Gutiérrez, C
Jiménez, B
Novo, V
机构
[1] Univ Nacl Educ Distancia, ETSI Ind, Dept Matemat Aplicada, Madrid 28040, Spain
[2] Univ Valladolid, ETSI Informat, Dept Matemat Aplicada, Valladolid, Spain
关键词
approximate solutions; epsilon-efficiency; max functions; epsilon-pareto optimality; epsilon-subdifferential;
D O I
10.1080/01630560500538789
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We consider a nondifferentiable convex multiobjective optimization problem whose feasible set is defined by affine equality constraints, convex inequality constraints, and an abstract convex set constraint. We obtain Fritz John and Kuhn-Tucker necessary and sufficient conditions for epsilon-Pareto optimality via a max function. We also provide some relations among epsilon-Pareto solutions for such a problem and approximate solutions for several associated scalar problems.
引用
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页码:57 / 70
页数:14
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