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

IF 0.9 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2025-09-11 DOI:10.1016/j.orl.2025.107366

Wang Chen , Yong Zhao , Liping Tang , Xinmin Yang

引用次数: 0

Abstract

This paper focuses on developing the conditional gradient algorithm with adaptive step size for multiobjective optimization problems on unbounded feasible regions. By employing the recession cone, we establish the well-defined nature of the algorithm. Under mild assumptions, we obtain the asymptotic convergence property and the iteration-complexity bound. Furthermore, a new variant of the algorithm is proposed, and the rate of convergence of this variant is obtained. Numerical experiments are conducted to verify the performance of the algorithms.

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无界多目标优化问题的条件梯度法的收敛性

研究了无界可行域上多目标优化问题的自适应步长条件梯度算法。通过使用衰退锥，我们建立了算法的良好定义性质。在温和的假设条件下，我们得到了该算法的渐近收敛性和迭代复杂度界。在此基础上，提出了该算法的一种新变体，并得到了该变体的收敛速度。通过数值实验验证了算法的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Operations Research Letters 管理科学-运筹学与管理科学

CiteScore

2.10

自引率

9.10%

发文量

111

审稿时长

83 days

期刊介绍： Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.