Portfolio Optimization Using Non-linear Inertia Weight PSO

摘要：

Inertia weight is one of the most important adjustable parameters of particle swarm optimization (PSO). The proper selection of inertia weight can prove a right balance between global search and local search. In this paper, a novel PSO with non-linear inertia weight based on the tangent function is provided. The performance of the proposed PSO models is compared with standard PSO with linearly-decrease inertia weight to solve an improved portfolio optimization model with complex constraints. The experimental results demonstrate that that the proposed PSO model is better than standard PSO in terms of convergence rate and solution precision.

关键词： particle swarm optimization inertia weight Tangent function portfolio optimization

作者: LI Li XUE Bing NTU Ben TAN Lijing

作者单位: College of Management. Shenzhen University, Shenzhen, P. R. China, 518100 Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, P. R. China, 230031 Measurement Specialties Inc, Shenzhen, P. R. China, 518100

会议类型: 国际会议

会议名称: 2010 International Conference on Management(2010管理国际大会)

会议地点: 上海

会议语种:英文

页码: 95-101

在线出版日期: 2010-07-24（万方平台首次上网日期，不代表论文的发表时间）