操作员(生物学)
算法
计算机科学
差异进化
数学优化
最优化问题
数学
生物化学
转录因子
基因
抑制因子
化学
作者
Karam M. Sallam,Saber M. Elsayed,Ripon K. Chakrabortty,Michael J. Ryan
标识
DOI:10.1109/cec48606.2020.9185577
摘要
In recent years, several multi-method and multi-operator-based algorithms have been proposed for solving optimization problems. Generally, their performance is better than other algorithms that based on a single operator and/or algorithm. However, they do not perform consistently well over all the problems tested in the literature. In this paper, we propose an improved optimization algorithm that uses the benefits of multiple differential evolution operators, with more emphasis placed on the best-performing operator. The performance of the proposed algorithm is tested by solving 10 problems with 5, 10, 15 and 20 dimensions taken from CEC2020 competition on single objective bound constrained optimization, with its results outperforming both single operator-based and different state-of-the-art algorithms.
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