计算机与数字工程2016，Vol.44Issue(8)：1407-1411,1415,6.DOI:10.3969/j.issn.1672-9722.2016.08.003
解复杂连续函数优化问题的动态量子遗传算法
Complex Continuous Function Optimization Problem of Dynamic Quantum Genetic Algorithm
摘要
Abstract
A complex continuous function optimization of dynamic quantum genetic algorithm (DQGA ) is studied .A dynamic update strategy of quantum rotation angle and quantum gate adjust strategy is designed to speed up the algorithm convergence speed ,at the same time for the elimination of poor fitness individuals ,the mutation operator dynamically is em-bedded in the quantum rotation strategy table .Introducing the cataclysm operator in the late evolution algorithm makes the algorithm timely and jump out of local optimum ,premature convergence is avoid .Five complex continuous functions of the test results show that the proposed algorithm’s optimization ability for optimization of complex continuous function is stron-ger than QGA ,the stability of the algorithm is higher ,the iteration number of the algorithm is superior to traditional quan-tum genetic algorithm .关键词
复杂连续函数优化/量子遗传算法/动态调整旋转角/灾变算子Key words
complex continuous function optimization/quantum genetic algorithm/dynamic adjusting rotation angle/the cataclysm operator分类
信息技术与安全科学引用本文复制引用
黄山,覃华,苏一丹,冯志新..解复杂连续函数优化问题的动态量子遗传算法[J].计算机与数字工程,2016,44(8):1407-1411,1415,6.基金项目
面向大规模不完备不一致数据的自适应粒化分类模型及高效分类方法研究（编号61363027）；教育部人文社会科学研究规划基金项目（编号11YJAZH080）资助。 （）
