On the convergence of conditional gradient method for unbounded multiobjective optimization problems

Fuente: arXiv
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Autori principali: Chen, Wang, Zhao, Yong, Tang, Liping, Yang, Xinmin
Natura: Preprint
Pubblicazione: 2024
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author Chen, Wang
Zhao, Yong
Tang, Liping
Yang, Xinmin
author_facet Chen, Wang
Zhao, Yong
Tang, Liping
Yang, Xinmin
contents This paper focuses on developing a conditional gradient algorithm for multiobjective optimization problems with an unbounded feasible region. We employ the concept of recession cone to establish the well-defined nature of the algorithm. The asymptotic convergence property and the iteration-complexity bound are established under mild assumptions. Numerical examples are provided to verify the algorithmic performance.
format Preprint
id arxiv_https___arxiv_org_abs_2403_02671
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On the convergence of conditional gradient method for unbounded multiobjective optimization problems
Chen, Wang
Zhao, Yong
Tang, Liping
Yang, Xinmin
Optimization and Control
This paper focuses on developing a conditional gradient algorithm for multiobjective optimization problems with an unbounded feasible region. We employ the concept of recession cone to establish the well-defined nature of the algorithm. The asymptotic convergence property and the iteration-complexity bound are established under mild assumptions. Numerical examples are provided to verify the algorithmic performance.
title On the convergence of conditional gradient method for unbounded multiobjective optimization problems
topic Optimization and Control
url https://arxiv.org/abs/2403.02671