Evolutionary programming based on uniform design with application to multiobjective optimization

Jihui Zhang, Junqin Xu
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引用次数: 4

Abstract

Pareto-optimality is one of the important methods to solve multiobjective optimization problems. It is desirable to find as much as possible Pareto-optimal solutions, and it is also highly expected to find the ones scattered uniformly over the Pareto frontier such that a variety of compromise solutions can be provided to the decision maker. For this purpose, an evolutionary programming algorithm, called evolutionary programming based on uniform design (UDEP), is proposed in this paper. Uniform design technique is used to define some fitness functions which can guide the search evenly toward the Pareto frontier. In order to overcome premature and provide as much as possible candidate solutions evenly scattered in the whole search space, uniform design technique, variable region search, as well as niche technique are used. Uniform design makes it possible to explore the search space evenly, while variable region search and niche technique help to keep diversity of the population. Their combination improves the search ability of EP (evolutionary programming) significantly. Many numerical experimental results show the usefulness of the proposed method.
基于均匀设计的进化规划及其在多目标优化中的应用
帕累托最优是求解多目标优化问题的重要方法之一。人们希望找到尽可能多的帕累托最优解,同时也希望找到均匀分布在帕累托边界上的解,以便为决策者提供各种折衷解。为此,本文提出了一种基于均匀设计的进化规划算法。采用均匀设计技术定义了一些适应度函数,使搜索均匀地指向Pareto边界。为了克服早熟问题,在整个搜索空间中提供尽可能多的均匀分布的候选解,采用了均匀设计技术、变区域搜索技术和小生境技术。均匀设计使搜索空间的均匀探索成为可能,而变区域搜索和小生境技术则有助于保持种群的多样性。它们的组合显著提高了进化规划的搜索能力。许多数值实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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