On the Analysis of Performance of the Artificial Tribe Algorithm

摘要：

Artificial Tribe Algorithm (ATA) is a novel intelligent optimization algorithm based on the simulation of bionic intelligent optimization algorithm. This work discusses the main factors which influence the performance of ATA, and compares the performance of ATA with that of genetic algorithm (GA), particle swarm optimization (PSO), and artificial fish-swarm algorithm (AFSA) for optimization multivariable functions. The simulation results showed that ATA outperforms the mentioned algorithms in global optimization problems.

关键词： artificial tribe algorithm bionic intelligent optimization algorithm genetic algorithm particle swarm algorithm artificial fish-swarm algorithm optimization

作者: Tanggong Chen Xiaowei Wei Wenhui Jia Zhi Liu

作者单位: Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin, China

会议类型: 国际会议

会议名称: The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

会议地点: 黄山

会议语种:英文

页码: 60-63

在线出版日期: 2010-05-28（万方平台首次上网日期，不代表论文的发表时间）