A GREEDY PARTICLE SWARM OPTIMIZATION FOR SOLVING KNAPSACK PROBLEM

摘要：

For solving knapsack problem (KP) with binary particle swarm optimization, this paper firstly proposes a new greedy transform method and gives a kind of effective implement algorithm.Then it combines the greedy transform method with binary particle swarm optimization with double-structure coding, advanced a new algorithm for solving KP: Greedy Particle Swarm Optimization (GPSO) which is a hybrid evolution algorithm.For a famous KP instance, GPSO got the best solution of the instance as far as know.It indicates that GPSO algorithm is a new and more effective method for knapsack problem.

关键词： Particle swarm optimization Knapsack problem Greedy transform method

作者: YI-CHAO HE LEI ZHOU CHUN-PU SHEN

作者单位: School of Information Engineering, Shijiazhuang University of Economics, Shijazhuang Hebei 050031,Ch Tangshan Industrial Vocation-Technical College, Tangshan Hebei 063020,China College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang 050016,China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 995-998

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）