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《Journal of Harbin Institute of Technology》 2009-06
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Virus-evolutionary particle swarm optimization algorithm for knapsack problem

GAO Fang,CUI Gang,WU Zhi-bo,LIU Hong-wei,YANG Xiao-zong(School of Computer Science and Technology,Harbin Institute of Technology,Harbin 150001,China)  
To improve the search capability of particle swarm algorithm,an improved discrete particle swarm optimization algorithm based on virus evolution theory is proposed and named as virus-evolutionary discrete particle swarm optimization (VEPSO) algorithm. Biological virus mechanism and the infection-based operation between host and virus are introduced in the particle swarm. Virus individual is coded with the same length as particle,and it executes infection and incorporation operations. The horizontal infection and vertical propagation of virus are fully used to maintain the individual diversity and local search capability in solution space. This algorithm is verified by solving knapsack problem. Simulation results show that the search capability of VEPSO algorithm is better than that of genetic algorithm,simulated annealing and standard PSO algorithm. This algorithm is able to effectively solve knapsack and other NP-hard problems.
【Fund】: 中国高技术研究发展计划重大资助项目(2006AA01A103)
【CateGory Index】: TP301.6
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