A Novel Swarm Optimization Algorithm Based On Social Force Model for Multimodal Functions

摘要：

Social Force model is a dynamic model used to the simulation of crowd behaviors. The Social Force model explains the formation of self-organization from the dynamic. In this paper, a new Swarm Optimization algorithm based on Social Force model (SFSO) is proposed. The SFSO algorithm is a population based optimization technique which is inspired from the behaviors of pedestrian. In SFSO algorithm, the searching characteristics of the pedestrians, such as target selecting, information exchange, overtaking search and scene understanding, are the special abstraction to the pedestrians’ movement and psychology. The results on benchmark problems indicated that SFSO is a promising optimization method and an effective approach to solve multimodal numerical optimization problems.

关键词： Social Force Model Swarm optimization SFSO algorithm Multimodal

作者: YAN Gao-wei LI Chuang-qin Lu Mu-chao

作者单位: Taiyuan University of Technology, Taiyuan, 030024

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 849-854

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）