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Network Based Linear Population Size Reduction in SHADE

机译:SHADE中基于网络的线性人口规模缩减

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摘要

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(SHADE)减少人口规模的新方法。当前的L-SHADE算法使用适应度函数值来选择将从当前总体中删除的个体。本文提出的算法变体(Net L-SHADE)是利用进化过程中的信息构建一个个体网络,并根据个体的中心度选择要删除的个体。将该技术与CEC2015基准测试集上的最新L-SHADE进行了比较,并报告了结果。

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