基于量子遗传的混合粒子群优化算法  

Hybrid particle swarm optimization algorithm based on quantum genetic

作　　者：赵莉[1] 董玉民[2] 

机构地区：[1]青岛理工大学计算机工程学院,山东青岛266033 [2]青岛理工大学网络中心,山东青岛266033

出　　处：《计算机工程与设计》2014年第7期2566-2571,共6页Computer Engineering and Design

基　　金：国家自然科学基金项目(61173056)

摘　　要：为提高智能优化算法的性能,将其更好地应用到各个领域,提出了一种两阶段优化算法。在改进的量子遗传算法的基础上,进一步结合粒子群优化算法,构造了量子遗传-粒子群混合算法。通过量子遗传算法对问题进行初步求解,将第一阶段的优化结果作为粒子群算法的初始值,进行第二阶段的问题求解过程,得到问题的最终优化解。通过实验将该算法与传统优化算法进行比较,实验结果表明,该算法在性能方面有一定程度的提高。To improve the performance of the intelligent optimization algorithm,making the optimization algorithm better appli-cable to various fields,a kind of two phase optimization algorithm was put forward.On the basis of the improved quantum gene-tic algorithm and further combined with particle swarm optimization algorithm,the quantum genetic-mixed particle swarm algo-rithm was constructed.First the problem was solved by quantum genetic algorithm preliminarily,and then the first stage optimi-zation results were taken as initial values for the second stage of the problem solving process to get the final optimization problem solution.The new hybrid algorithm was compared with the traditional optimization algorithm,the experimental results showed that the performance of the new algorithm had certain degree of improvement.

关 键 词：智能优化算法 量子遗传 粒子群算法 最优化 混合算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]