Geometric Duality for Convex Vector Optimization Problems

被引：0
|
作者：
Heyde, Frank [1 ]
机构：
[1] Tech Univ Bergakad Freiberg, Fak Math & Informat, D-09596 Freiberg, Germany
来源：
JOURNAL OF CONVEX ANALYSIS | 2013年 / 20卷 / 03期
关键词：
Geometric duality theory; vector optimization; Legendre-Fenchel conjugate; second-order subdifferential; Dupin indicatrix; 2ND DERIVATIVES;
D O I：
暂无
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
Geometric duality theory for multiple objective linear programming problems turned out to be very useful for the development of efficient algorithms to generate or approximate the whole set of nondominated points in the outcome space. This article extends the geometric duality theory to convex vector optimization problems.
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页码：813 / 832
页数：20
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