多目标优化的部分优势法实证分析

A. Engelbrecht, Mardé Helbig
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引用次数: 3

摘要

对标准多目标优化问题的研究表明,多目标优化算法很难解决三个以上目标的优化问题,因为许多解决方案都会被支配。因此,对于多目标优化问题来说,帕累托支配关系在指导搜索以找到最佳帕累托前沿方面不再有效。最近,有人提出了一种部分支配方法,以解决在许多目标上应用支配关系所遇到的问题。初步结果表明,这种部分支配关系很有前景,而且随着目标数量的增加,其扩展性也很好。本文对部分支配关系进行了更广泛的实证分析,并将其与最先进的算法进行了比较。结果进一步说明,部分支配关系是解决多目标优化问题的有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Empirical Analysis of A Partial Dominance Approach to Many-Objective Optimisation
Studies on standard many-objective optimisation problems have indicated that multi-objective optimisation algorithms struggle to solve optimisation problems with more than three objectives, because many solutions become dominated. Therefore, the Paretodominance relation is no longer efficient in guiding the search to find an optimal Pareto front for many-objective optimisation problems. Recently, a partial dominance approach has been proposed to address the problem experienced with application of the dominance relation on many objectives. Preliminary results have illustrated that this partial dominance relation has promise, and scales well with an increase in the number of objectives. This paper conducts a more extensive empirical analysis of the partial dominance relation on a larger benchmark of difficult many-objective optimisation problems, in comparison to state-of-the-art algorithms. The results further illustrate that partial dominance is an efficient approach to solve many-objective optimisation problems.
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