Searching the Optimal Rush Repair Path of Power Lines Based on an Improved Particle Swarm Optimization Algorithm

摘要：

On the basis of the analysis and research on the optimal rush repair path of power lines, this paper proposed an improved particle swarm algorithm to search the optimal rush repair path, which is entropy-based adaptive mutation particle swarm algorithm. Particle swarm algorithm is a stochastic global optimization technique. It has been applied in many areas and got extensive research, because PSO algorithm can be implemented with ease and has few parameters which need to be adjusted. But the standard particle swarm algorithm still exist the problem of premature convergence. Therefore the improved PSO introduced entropy to evaluate population diversity, and adaptively adjusted mutation rate and mutation operator based on population diversity, further uses mutation operation to enrich population diversity, enlarge search space, and avoid to fall into local optimal solution. The simulation experiments demonstrate that while searching the optimal rush repair path, the entropy-based adaptive mutation has better superiority and practicability.

关键词： particle swarm algorithm adaptive mutation optimal rush repair path entropy

作者: Zhu Yongli Chen Yingwei

作者单位: School of computer science and technology in North China Electric Power University, Baoding, Hebei

会议类型: 国际会议

会议名称: The International Conference on Electrical Engineering 2009(2009 电机工程国际会议)

会议地点: 沈阳

会议语种:英文

页码: 1-6

在线出版日期: 2009-07-05（万方平台首次上网日期，不代表论文的发表时间）