【摘要】 提出一种基于正交试验设计的量子进化算法.通过正交试验设计方法找到最有效的优秀个体知识组合,利用基于正交试验因素分析的约束修补算子对知识组合进行修补,并将获得的知识组合作为量子群体的吸引子.同时,采用正交试验结果动态调节量子更新转角大小,使得量子更新更简洁且具有自适应学习能力.Rastrigin和Ackley函数优化和0-1背包组合优化实验表明:该算法缩短了量子寻找到最佳知识组合的时间,降低了计算成本,提高了算法精度.更多还原

【Abstract】 A novel quantum-inspired evolutionary algorithm based on orthogonal experimental design method was proposed.By using orthogonal experiment on different excellent individuals,the algorithm can get a better knowledge combination.A new repair operator based on orthogonal experimental factor analysis was proposed for the knowledge combination which does not satisfy the constraint conditions.The result of the knowledge combination was used as a new attractor for quantum individuals.In addition,the quantum individuals were updated by new rotation gates base on the result of the orthogonal experiment.The proposed updating of quantum can simply self-adaptively adjust length during evolution.This algorithm was tested with Rastrigin,Ackley benchmark functions and 0-1 knapsack problem.The results show that the algorithm shortens the time to find the best knowledge combination and improves the accuracy of the algorithm.更多还原