A relaxed projection method for solving multiobjective optimization problems

被引：17
|
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.
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页码：17 / 23
页数：7
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