渡线
数学优化
蝴蝶
协方差矩阵
计算机科学
基质(化学分析)
CMA-ES公司
人口
操作员(生物学)
相(物质)
算法
水准点(测量)
数学
协方差矩阵的估计
人工智能
生态学
地理
物理
抑制因子
大地测量学
材料科学
化学
复合材料
量子力学
人口学
社会学
生物化学
基因
生物
转录因子
作者
Abhishek Kumar,Rakesh R. Misra,Devender Singh
出处
期刊:Congress on Evolutionary Computation
日期:2017-06-01
被引量:114
标识
DOI:10.1109/cec.2017.7969524
摘要
Effective Butterfly Optimizer(EBO) is a self-adaptive Butterfly Optimizer which incorporates a crossover operator in Perching and Patrolling to increase the diversity of the population. This paper proposes a new retreat phase called Covariance Matrix Adapted Retreat Phase (CMAR), which uses covariance matrix to generate a new solution and thus improves the local search capability of EBO. This version of EBO is called EBOwithCMAR. We evaluated the performance of EBOwithCMAR on CEC-2017 benchmark problems and compared with the results of winners of a special session of CEC-2016 for bound-constrained problems. The experimental results show that EBOwithCMAR is competitive with the compared algorithms.
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