单元超曲面上生成的参考点

Haruto Takeuchi, Md. Kawsar Khan, M. Ohki
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引用次数: 0

摘要

提出了一种多目标优化进化算法在超曲面上统一生成参考点的方法。最近,人们提出了利用参考点集来获得多维目标空间中的选择压力的maoea方法,但是没有一种方法可以生成包含用户取向的参考点集。提出了一种多维目标空间中单位超球和单位超平面上均匀参考点的生成方法。采用非支配排序遗传算法(NSGA-III)求解多目标遗传规划(GP)问题,采用基于分解的多目标进化算法(MOEA/D)求解多目标组合优化问题。结果表明,与传统方法相比,该方法的结果不差。由于所提出的方法可以很容易地结合用户导向,这表明了所提出方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reference Points Generated on Unit Hypersurfaces for MaOEAs
This paper proposes a method to uniformly generate reference points on a hypersurface for many-objective optimization evolutionary algorithms (MaOEAs). Recently, MaOEAs have been proposed to obtain selection pressure in a multidimensional objective space by using a reference point set, but there is no method for generating a reference point set that is supposed to incorporate user orientation. This paper proposes a method for generating uniform reference points on unit hyperspheres and unit hyperplanes in a multidimensional objective space. The proposed method is applied to the multi-objective genetic programming (GP) problem by non-dominated sorting genetic algorithm-III (NSGA-III) and to the multi-objective combinatorial optimization problem by multiobjective evolutionary algorithm based on decomposition (MOEA/D). As a result, we confirm that the proposed method gives non-inferior results compared to conventional methods. Since the proposed method can easily incorporate user orientation, this shows the effectiveness of the proposed method.
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