Optimality and mixed saddle point criteria in multiobjective optimization

被引:24
|
作者
Bhatia, Guneet [1 ]
机构
[1] Univ Delhi, Dept Math, Delhi 110007, India
关键词
higher order strong convexity; strict minimizers; partial Lagrangian; mixed saddle;
D O I
10.1016/j.jmaa.2007.11.042
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, higher order strong convexity for Lipschitz functions is introduced and is utilized to derive the optimality conditions for the new concept of strict minimizer of higher order for a multiobjective optimization problem. Variational inequality problem is introduced and its solutions are related to the strict minimizers of higher order for a multiobjective optimization problem. The notion of vector valued partial Lagrangian is also introduced and equivalence of the mixed saddle points of higher order and higher order minima are provided. (C) 2007 Elsevier Inc. All rights reserved.
引用
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页码:135 / 145
页数:11
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