A relaxed projection method for solving multiobjective optimization problems

被引：19

作者：

Brito, A. S. ^{[1
]}

Cruz Neto, J. X. ^{[2
]}

Santos, P. S. M. ^{[3
]}

Souza, S. S. ^{[3
]}

机构：

[1] DM Univ Estadual Piaui, Teresina, Brazil

[2] Univ Fed Piaui, DM, BR-64049500 Teresina, PI, Brazil

[3] Univ Fed Piaui, CMRV, BR-64049500 Parnaiba, PI, Brazil

来源：

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH | 2017年 / 256卷 / 01期

关键词：

Multiple objective programming; Pareto optimality; Projected subgradient method; STEEPEST DESCENT METHOD; VECTOR OPTIMIZATION; VARIATIONAL-INEQUALITIES; MULTICRITERIA OPTIMIZATION; SUBGRADIENT METHOD; PROXIMAL METHODS; CONVEX-PROGRAMS; ALGORITHM; NONSMOOTH; CONVERGENCE;

D O I：

10.1016/j.ejor.2016.05.026

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

In this paper, we propose an algorithm for solving multiobjective minimization problems on nonempty closed convex subsets of the Euclidean space. The proposed method combines a reflection technique for obtaining a feasible point with a projected subgradient method. Under suitable assumptions, we show that the sequence generated using this method converges to a Pareto optimal point of the problem. We also present some numerical results. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：17 / 23

页数：7

共 32 条

[11] A steepest descent method for vector optimization [J].