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A mean shift assisted differential evolution algorithm

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

It is well known that Differential Evolution (DE) algorithm has been widely applied to solve global optimization problems during the last decades. DE is usually criticized for the slow convergence. To improve the algorithm performance, we propose an algorithm called MSDE that utilizes a local search operator based on mean shift. In MSDE, one offspring solution is generated by the mean shift based search operator, and the others are created by the DE search operator. A test suite of 12 benchmark functions with different characteristics are chosen to evaluate our approach. The experimental results suggest that MSDE can successfully improve the performance of DE and have a faster convergence rate on the given test suite.

源语言英语
主期刊名Bio-inspired Computing – Theories and Applications - 11th International Conference, BIC-TA 2016, Revised Selected Papers
编辑Linqiang Pan, Maoguo Gong, Tao Song, Gexiang Zhang, Tao Song
出版商Springer Verlag
163-172
页数10
ISBN(印刷版)9789811036132
DOI
出版状态已出版 - 2016
活动11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016 - Xian, 中国
期限: 28 10月 201630 10月 2016

出版系列

姓名Communications in Computer and Information Science
682
ISSN(印刷版)1865-0929

会议

会议11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016
国家/地区中国
Xian
时期28/10/1630/10/16

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