Quantum Dynamic Mechanism-based Multi-objective Evolutionary Algorithm and Performance Analysis

摘要：

A novel Self-organizing Quantum Evolutionary Algorithm for Multi-objective optimization(MSQEA) is proposed. The technique for improving the performance of MSQEA has been described. By using self-organizing co-evolution strategy each subpopulation can obtain more optimal solutions. Because of the quantum dynamic mechanism all the subpopulations may move concurrently in a force-field until all of them reach their equilibrium states. Self-organizing algorithm has advantages in terms of the adaptability; reliability and the learning ability over traditional organizing algorithm, so the solution quality is improved. 0/1 Multi-objective knapsack problem simulation results demonstrate the superiority of MSQEA in this paper.

关键词： Quantum evolutionary algorithm Multi-objective optimization co-evolutionary strategy quantum dynamic mechanism

作者: Xiaoming You Xiankun Sun Sheng Liu Jiaying Huang

作者单位: College of Electronic and Electrical Engineering,Shanghai University of Engineering Science Shanghai,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 429-432

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）