GSO:An Improved PSO Based on Geese Flight Theory

摘要：

　　Formation flight of swan geese is one type of swarm intelligence developed through evolution by natural selection.The research on its intrinsic mechanism has great impact on the bionics field.Based on previous research achievements, extensive observation and analysis on such phenomenon, five geese-flight rules and hypotheses are proposed in order to form a concise and simple geese-flight theory framework in this paper.Goose Swarm Optimization algorithm is derived based on the Standard Particle Swam Optimization algorithm.Experimental results show that GSO algorithm is superior in several aspects, such as convergence speed, convergence precision, robustness and etc.The theory offers the in-depth explanations for the performance superiority.Moreover, the rules and hypotheses for formation flight adhere to all five basic principles of swarm intelligence.Therefore, the proposed geese-flight theory is highly rational and has important theoretical innovations, and GSO algorithm can be utilized in a wide range of applications.

关键词： Geese Theory Goose Swarm Optimization Particle Swarm Optimization Swarm Intelligence

作者: Shengkui Dai Peixian Zhuang Wenjie Xiang

作者单位: College of Information Science and Engineering of National HuaQiao University

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 87-95

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）