计算机工程与应用2011，Vol.47Issue(20)：34-37,4.DOI:10.3778/j.issn.1002-8331.2011.20.010
一种改进的量子粒子群优化算法及其应用
Improved quantum particle swarm optimization algorithm and its application
摘要
Abstract
In order to enhance the optimization efficiency of quantum particle swarm optimization coding based on the probability amplitude, an improved quantum particle swarm optimization is proposed.In the proposed algorithm, the mutation of particle position is performed by quantum Hadamard-gate, the exchange mutation of probability amplitude is improved into the rotation adjustment with better flexibility, and this avoids the loss of population diversity in search space.By studying the relationship among inertia factors, self-factors and global-factors, an adaptive determination method of the global-factors according to the current fitness is proposed.With application of function extremum optimization, the simulation results show that the proposed algorithm is superior to the original one in both search capability and optimization efficiency.关键词
粒子群优化/变异/自适应调整/优化算法Key words
particle swarm optimization/ mutation/ adaptive adjustment/ optimization algorithm分类
信息技术与安全科学引用本文复制引用
许少华,王皓,王颖,李盼池..一种改进的量子粒子群优化算法及其应用[J].计算机工程与应用,2011,47(20):34-37,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60572174) （the National Natural Science Foundation of China under Grant No.60572174）
黑龙江省自然科学基金(No.ZA2006-11). （No.ZA2006-11）
