计算机工程与应用2013，Vol.49Issue(6)：253-256,261,5.DOI:10.3778/j.issn.1002-8331.1111-0310
基于捕食策略的粒子群算法求解投资组合问题
Particle Swarm Optimization based on Predatory Search for portfolio investment
摘要
Abstract
A portfolio investment model considering the complete trade expenses is built through analyzing the actual investment environment and characteristic. For the weakness that the standard Particle Swarm Optimization easily falls into local optimum and search precision faults, the Particle Swarm Optimization based on Predatory Search is raised to solve the portfolio investment model. Predatory search strategy can control the search space of the particle swarm through adjusting the level of restriction. Thereby, the global search and local search can be balanced. The algorithm is proven effective through an empirical analysis.关键词
捕食搜索策略/粒子群算法/投资组合模型Key words
predatory search strategy/ Particle Swarm Optimization(PSO)/ portfolio investment分类
管理科学引用本文复制引用
刘冬华,甘若迅,樊锁海,杨明华..基于捕食策略的粒子群算法求解投资组合问题[J].计算机工程与应用,2013,49(6):253-256,261,5.基金项目
国家自然科学基金(No.11071089) （No.11071089）
广东省自然科学基金(No.10151063201000006) （No.10151063201000006）
中央高校基本业务费专项资金(No.21609602). （No.21609602）
