双目标整数线性鲁棒优化方法

IF 6 2区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Fabian Chlumsky-Harttmann, Marie Schmidt, Anita Schöbel
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引用次数: 0

摘要

现实世界的优化问题往往不仅涉及多个目标,而且还涉及不确定参数。在这种情况下,目标是找到鲁棒的帕累托最优解,即在不确定数据的所有可能实现下都相当好。在过去的十年中,这种解决方案已经在许多论文中进行了研究,并被称为鲁棒高效。然而,寻找鲁棒高效解的求解方法很少。本文给出了确定双目标混合整数线性鲁棒优化问题鲁棒有效解的三种算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approaches for biobjective integer linear robust optimization
Real-world optimization problems often do not just involve multiple objectives but also uncertain parameters. In this case, the goal is to find Pareto-optimal solutions that are robust, i.e., reasonably good under all possible realizations of the uncertain data. Such solutions have been studied in many papers within the last ten years and are called robust efficient. However, solution methods for finding robust efficient solutions are scarce. In this paper, we develop three algorithms for determining robust efficient solutions to biobjective mixed-integer linear robust optimization problems.
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来源期刊
European Journal of Operational Research
European Journal of Operational Research 管理科学-运筹学与管理科学
CiteScore
11.90
自引率
9.40%
发文量
786
审稿时长
8.2 months
期刊介绍: The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making.
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