期刊
2018 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
卷 -, 期 -, 页码 757-764出版社
IEEE
DOI: 10.1109/CEC.2018.8477977
关键词
LSHADE; selective pressure; covariance matrix; optimization; crossover; mutation.
类别
资金
- Ministry of Education and Science of Russian Federation [2.1680.2017/pi]
Solving single-objective real-parameter optimization problems can still cause difficulties, for example if the optimized function is multimodal or has rotated trap problems. Such optimization problems can be found in various areas in real-world applications. Usually, these problems are very complex and computationally expensive. A new algorithm, which is a modification of the LSHADE algorithm with a rank-based selective pressure strategy, called LSHADE-RSP, is presented in this paper. The proposed algorithm is a new variant of the LSHADE algorithm, the basic idea of which consists in the adaptation of its mutation strategy using selective pressure. The experiments were performed on CEC 2018 benchmark functions. A comparison of the proposed LSHADE-RSP algorithm and the algorithm-participants of the CEC 2017 competition is presented. From the obtained results it can be concluded that LSHADERSP performs better in comparison with most alternative algorithms: using the CEC 2018 evaluation method, LSHADERSP obtained one of the best final scores among the algorithms that were winners of the previous competition.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据