表征非凸多目标优化问题的弱有效解集的非空旷性和紧凑性

IF 0.8 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2024-02-19 DOI:10.1016/j.orl.2024.107092

Gang Wang, Yihan Fu

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引用次数: 0

摘要

本文证明，当且仅当有限标量优化问题在温和条件下具有非空且紧凑的弱效率解集时，非凸多目标优化问题才具有非空且紧凑的弱效率解集，从而部分缩小了非凸多目标问题与凸多目标问题在表征弱效率解集的非空性和紧凑性方面的差距。本文举了两个例子来证明这一结论。

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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Characterizing the nonemptiness and compactness of weakly efficient solution sets for non-convex multiobjective optimization problems

In this paper, we demonstrate that non-convex multiobjective optimization problems have nonempty and compact weakly efficient solution sets if and only if finite scalar optimization problems have nonempty and compact solution sets under mild conditions, which partially reduces the gap between non-convex and convex multiobjective problems in characterizing the nonemptiness and compactness of weakly efficient solution sets. Two examples are provided to support the findings.

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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.