Hybrid Dynamical Evolutionary Algorithm and Time Complexity Analysis

摘要：

The dynamical evolutionary algorithm (DEA) is a new evolutionary algorithm based on the theory of statistical mechanics, however, DEA converges slowly and often converge at local optima for some function optimization problems. In this paper, a hybrid dynamical evolutionary algorithm (HDEA) with multiparent crossover and differential evolution mutation is proposed for accelerating convergence velocity and easily escaping suboptimal solutions. Moreover, the population of HDEA is initialized by chaos. In order to confirm the effectiveness of our algorithm, HDEA is applied to solve the typical numerical function minimization problems. The computational complexity of HDEA is analyzed, and the experimental results show that HDEA outperforms the DEA in the aspect of convergence velocity and precision, even the two algorithms have the similar time complexity.

关键词： dynamical evolutionary algorithm chaos multi-parent crossover differential evolution time complexity

作者: Huiying LI

作者单位: School of Information Engineering Jingdezhen Ceramic Institute Jingdezhen, China

会议类型: 国际会议

会议名称: 2010 International Conference on Circuit and Signal Processing(2010年电路与信号处理国际会议 ICCSP 2010)

会议地点: 上海

会议语种:英文

页码: 377-380

在线出版日期: 2010-12-25（万方平台首次上网日期，不代表论文的发表时间）