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Network Based Linear Population Size Reduction in SHADE

机译:基于网络的线性群体尺寸减小阴影

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This research paper presents a new approach to population size reduction in Success-History based Adaptive Differential Evolution (SHADE). The current L-SHADE algorithm uses fitness function value to select individuals which will be deleted from the current population. Algorithm variant proposed in this paper (Net L-SHADE) is using the information from evolutionary process to construct a network of individuals and the ones which would be deleted are selected based on their degree of centrality. The proposed technique is compared to state-of-art L-SHADE on CEC2015 benchmark set and the results are reported.
机译:本研究论文提出了一种基于成功历史的自适应差分进化(阴影)的人口大小减少了一种新方法。当前L-SHADE算法使用健身功能值来选择将从当前群体中删除的单个。本文中提出的算法变型(NET L-SHADE)正在使用来自进化过程的信息来构建个人网络的网络,并且基于其中心性程度选择将被删除的网络。将所提出的技术与CEC2015基准组上的最先进的L-SHADE进行比较,并报告结果。

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