A Quantum Differential Evolution Algorithm for Function Optimization

摘要：

In this paper, we propose a quantum differential evolution (QDE) algorithm for function optimization, which can improve the performance of differential evolution (DE) algorithm. First, the algorithm does some basic operations, such as mutation, crossover and selection of vectors. And then a quantum computing method is utilized to search the global optimal solutions, which avoids falling into the local minimums. Our experimental results show the proposed algorithm is feasible. And compared with other algorithms, the proposed algorithm is more effective. Furthermore it can improve the speed of convergence.

关键词： differential evolution quantum computing function optimization

作者: Qiuyan Xu Jun Guo

作者单位: Computer Center East China Normal University 3663 Zhong Shan Rd.N., 200062 Shanghai, China College of Information Engineering Yancheng Institute of Technology 9 Xi Wang Rd., 224051 Yancheng,

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 347-350

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）