A Simple and Fast Differential Evolution for Unconstraine Global Optimization

摘要：

Differential evolution (DE) has recently been successfully applied to solve a wide range of numerical optimization problems. However, their solutions may still be far away from the optimal value. This paper proposes a simple and effectual differential evolution algorithm, and then it is used to solve the unconstrained function optimization. The new algorithm introducing hybrid multi-parent crossover-mutation and new evolution strategy, using randomized scaling factor. The new algorithm is tested on 23 well-known benchmark functions and compared with the fast evolutionary programming (FEP), fast evolution strategy (FES) and original DE (ODE),The experimental results show that the proposed algorithm is robust and has higher accuracy than existing algorithms.

关键词： Differential evolution evolutionary algorithm multi-parent crossover-mutation global optimization

作者: Wenyin Gong Zhihua Cai Yongqin Huang

作者单位: School of Computer Science, China University of Geosciences, Wuhan 43007 P.R.China

会议类型: 国际会议

会议名称: The Second International Symposium on Intelligence Computation and Applications(ISICA 2007)(第二届智能计算及其应用国际会议)

会议地点: 武汉

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）