多目标问题的优化综合多项式变异算子类

Kent McClymont, E. Keedwell
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引用次数: 1

摘要

本文提出了一种新的方法来生成新的概率分布量身定制的特定问题类,用于优化突变算子。使用所提出的技术创建了一系列具有不同行为的定制算子,并且发现进化的多模态多项式分布与调谐高斯分布的性能相匹配,当应用于一个简单的(1+1)进化策略中的突变算子时。生成的启发式显示了DTLZ测试问题1、2和7的一系列理想特征;比如收敛速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimising multi-modal polynomial mutation operators for multi-objective problem classes
This paper presents a novel method of generating new probability distributions tailored to specific problem classes for use in optimisation mutation operators. A range of tailored operators with varying behaviours are created using the proposed technique and the evolved multi-modal polynomial distributions are found to match the performance of a tuned Gaussian distribution when applied to a mutation operator incorporated in a simple (1+1) Evolution Strategy. The generated heuristics are shown to display a range of desirable characteristics for the DTLZ test problems 1, 2 and 7; such as speed of convergence.
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