摘要
针对目前粒子群优化(PSO)算法理论基础薄弱,算法本质的分析还未形成体系的问题,从微观的角度出发,以量子力学为基础,提出并建立了粒子群优化算法的量子模型。模型采用无限深方势阱为分析背景,将算法的搜索过程解释为量子状态的转换,并通过模型解释算法执行过程中的内部机制,最后通过实验证明了所提出PSO算法寻优的量子本质。
As for the weak theoretical foundation of the Particle Swarm Optimization(PSO) algorithm and its analysis of the nature of the problem having not yet formed system,a new quantum model was established,which was based on quantum mechanics from the microscopic point of view.This model defined the search process as quantum state transition that in infinitely deep potential well.Through the model,the internal mechanism of executing process interpreted,and the experimental results show that the proposed algorithm has the optimization of quantum nature.
出处
《计算机应用》
CSCD
北大核心
2011年第A02期50-53,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(60702075)
四川省青年科学基金资助项目(09ZQ026-068)
关键词
群体智能
粒子群优化算法
全局优化
量子模型
无限深方势阱
swarm intelligence
Particle Swarm Optimization(PSO) algorithm
global optimization
quantum model
infinitely deep potential well