Differential Evolution Based on A Novel Double-Population Strategy

摘要：

Differential evolution (DE) is a population-based stochastic search algorithm, which shows good performance when solving many optimization problems. In order to improve the performance of DE, this paper presents a new variant of DE based on a doublepopulation strategy. The proposed approach is called DPDE, which consists of two populations. The first population focuses on original DE algorithm, and the second one concentrates on local search. To verify the performance of DPDE, ten famous benchmark functions were selected in the experiments. Simulation results show that DPDE outperforms DE and another variant of DE on most test functions.

关键词： differential evolution double-population local search function optimization

作者: Chen Chen

作者单位: Modern Education Technology and Information Center Lanzhou Commercial College Lanzhou 730020, China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 2330-2333

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）