An Improved GAFSA Based on Chaos Search and Modified Simplex Method

摘要：

　　This paper combines the dynamically adjusting parameters,the chaos search(CS),and the modified simplex method(MS)with GAFSA,and the CS_MS_GAFSA is proposed.The algorithm speeds up the convergence by dynamically adjusting the parameters,and increases the probability of artificial fish escaping local extreme points by chaotic search for the current global optimum value.When the algorithm converges to the global optimum nearby,a simplex is constructed and the algorithm switches to MS which will continue to optimize until a certain stop condition is satisfied.Take the best point of simplex vertex at this time as the optimal value.The computational results on benchmark functions show that CS_MS_GAFSA does improve in optimizing accuracy and convergence speed.

关键词： Artificial fish swarm algorithm(GAFSA) Global optimization Dynamically adjusting parameters Chaos search Modified simplex method

作者: Pei-zhen Peng Jie Yuan Zhao-jia Wang Yi Yu Min Jiang

作者单位: Key Laboratory of Measurement and Control of Complex Engineering of Ministry of Education,School of Automation,South East University,Nanjing,Jiangsu,China

会议类型: 国际会议

会议名称: The 2015 Chinese Intelligent Automation Conference(2015中国智能自动化会议)

会议地点: 福州

会议语种:英文

页码: 133-141

在线出版日期: 2015-05-08（万方平台首次上网日期，不代表论文的发表时间）