An away-step Frank-Wolfe algorithm for constrained multiobjective optimization

被引：0

作者：

Goncalves, Douglas S. ^{[1
]}

Goncalves, Max L. N. ^{[2
]}

Melo, Jefferson G. ^{[2
]}

机构：

[1] Univ Fed Santa Catarina, Dept Matemat, BR-88040900 Florianopolis, SC, Brazil

[2] Univ Fed Goias, IME, BR-74001970 Goiania, Go, Brazil

来源：

COMPUTATIONAL OPTIMIZATION AND APPLICATIONS | 2024年 / 88卷 / 03期

关键词：

Frank-Wolfe algorithm; Conditional gradient method; Away-step; Linear convergence rate; Pareto optimality; Constrained multiobjective problem; PROJECTED GRADIENT-METHOD; CONVERGENCE;

D O I：

10.1007/s10589-024-00577-5

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：

In this paper, we propose and analyze an away-step Frank-Wolfe algorithm designed for solving multiobjective optimization problems over polytopes. We prove that each limit point of the sequence generated by the algorithm is a weak Pareto optimal solution. Furthermore, under additional conditions, we show linear convergence of the whole sequence to a Pareto optimal solution. Numerical examples illustrate a promising performance of the proposed algorithm in problems where the multiobjective Frank-Wolfe convergence rate is only sublinear.

引用

页码：759 / 781

页数：23

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