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Niche-clearing-based Variable Mesh Optimization for multimodal problems

机译:基于利基清算的可变网格优化,用于多模式问题

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The development of niching methods is a very active research area within multimodal optimization. It includes not only the creation of new methods, but the formalization of hybrid methodologies resulting from the application of basic niching techniques to global optimization metaheuristics. In this paper, we discuss some preliminary results of a recently proposed metaheuristic algorithm, Variable Mesh Optimization (VMO), in the context of multimodal problems. To overcome some of the encountered limitations, a revamped version called Niche-Clearing-based Variable Mesh Optimization (NC-VMO) is put forth. NC-VMO demonstrated its ability to optimize multimodal functions by using a niche clearing technique. Experimental results confirm that the proposed approach is also competitive with other niche-based optimization methods in the literature.
机译:征地方法的发展是多峰优化中的一个非常活跃的研究区域。 它不仅包括新方法的创建,而且包括杂种方法的形式化,该方法是由于应用基本的效力技术对全球优化的成分训练。 在本文中,我们在多模式问题的背景下讨论了最近提出的成群质算法,可变网格优化(VMO)的一些初步结果。 为了克服一些遇到的限制,提出了一种名为基于Niche-Clearing的变量网格优化(NC-VMO)的改进版本。 NC-VMO证明了通过使用利基清算技术来优化多模函数的能力。 实验结果证实,该方法也与文献中的其他基于利基的优化方法竞争。

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