Duality in nonlinear multiobjective programming using augmented Lagrangian functions

被引：9

作者：

Singh, C

Bhatia, D

Rueda, N

机构：

[1] UNIV DELHI,SGTB KHALSA COLL,DEPT MATH,DELHI 110007,INDIA

[2] MERRIMACK COLL,DEPT MATH & COMP SCI,N ANDOVER,MA 01845

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 1996年 / 88卷 / 03期

关键词：

augmented Lagrangians; Pareto efficiency; weak duality; strong duality; concavity;

D O I：

10.1007/BF02192203

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

A vector-valued generalized Lagrangian is constructed for a nonlinear multiobjective programming problem. Using the Lagrangian, a multiobjective dual is considered. Without assuming differentiability, weak and strong duality theorems are established using Pareto efficiency.

引用

页码：659 / 670

页数：12

共 16 条

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Bertsekas D. P., 2019, Reinforcement learning and optimal control

[2] DUALITY FOR NON-LINEAR MULTIPLE-CRITERIA OPTIMIZATION PROBLEMS [J].