计算机工程与应用2012，Vol.48Issue(1)：44-46,56,4.DOI:10.3778/j.issn.1002-8331.2012.01.013
求解背包问题的混合粒子群优化算法
Hybrid particle swarm optimization algorithm for solving knapsack problem
王晓华 1沐爱勤 2刘金波2
作者信息
- 1. 中国矿业大学计算机学院,江苏徐州221008
- 2. 徐州空军学院基础部,江苏徐州221000
- 折叠
摘要
Abstract
A new genetic idea that offspring's gene is decided by its parent's, rather than produced by a simple cross is proposed. According to this idea, two methods of producing offspring with genetic probability are produced and they are combined with the particle swarm optimization respectively. The two hybrid particle swarm optimizations are applied to solving knapsack problem, and their performances are compared by normal numerical experiments. The validity of two hybrid algorithms is verified and the impacts of mutation probability on the algorithms are analyzed.关键词
粒子群优化算法/背包问题/遗传概率Key words
particle swarm optimization/knapsack problem/genetic probability分类
信息技术与安全科学引用本文复制引用
王晓华,沐爱勤,刘金波..求解背包问题的混合粒子群优化算法[J].计算机工程与应用,2012,48(1):44-46,56,4.
