An adaptive step improved fruit fly optimization algorithm

摘要：

　　In order to solve the shortcomings of Fruit Fly Optimization Algorithm(FOA),which is slow and easy to fall into local optimum,can not specify the domain,Fruit Fly Optimization Algorithm and logstic function transformation are combined to propose an adaptive step improved fruit fly optimization algorithm with logistic transform(ASFOALT).The algorithm improves the correctness of the optimal solution range by improving the fitness function of the FOA,and improves the overall performance of the algorithm by adding the adaptive step mechanism.The experimental results show that ASFOALT has a large improvement in global search capability,convergence speed,convergence accuracy and reliability.

关键词： fruit fly optimization algorithm self-adaptive step length

作者: Liu Kaiyuan Xie Dongqing

作者单位: School of Computer Science and Educational Software,GuangZhou University,GuangZhou 510006,China

会议类型: 国际会议

会议名称: The 3rd International Conference on Intelligent Energy and Power Systems (IEPS 2017)(第三届智能能源和电力系统国际会议)

会议地点: 杭州

会议语种:英文

页码: 126-134

在线出版日期: 2017-04-15（万方平台首次上网日期，不代表论文的发表时间）