多目标优化的非支配排序遗传算法改进

2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007) Pub Date : 2007-12-15 DOI:10.1109/CIS.WORKSHOPS.2007.192

V. S. Ghomsheh, M.A. Khanehsar, M. Teshnehlab

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引用次数: 13

摘要

非支配排序遗传算法- ii (NSGA-II)是一种相对较新的技术，用于寻找或近似多目标优化问题的帕累托最优集。在不同的研究中，NSGA-II与其他多目标进化算法相比表现出了良好的性能(Deb et al.， 2002)。本文提出了一个改进版本，命名为nicching - nsga - ii (n-NSGA-II)。该算法采用非支配排序后的新方法来保持多样性。n-NSGA-II与NSGA-II等方法对ZDT测试问题的比较得到了很好的结果。

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Improving the Non-dominate Sorting Genetic Algorithm for Multi-objective Optimization

The non-dominate sorting genetic algorithmic-II (NSGA-II) is a relatively recent technique for finding or approximating the Pareto-optimal set for multi-objective optimization problems. In different studies NSGA-II has shown good performance in comparison to other multi-objective evolutionary algorithms (Deb et al., 2002). In this paper an improved version which is named Niching-NSGA-II (n-NSGA-II) is proposed. This algorithm uses new method after non-dominate sorting procedure for keeping diversity. The comparison of n-NSGA-II with NSGA-II and other methods on ZDT test problems yields promising results.

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2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)

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