A Novel Memetic Algorithm Based on Real-Observation Quantum-Inspired Evolutionary Algorithms

摘要：

To enhance the local search capability of quantum-inspired evolutionary algorithm,a novel MemeticAlgorithm based on real-observation Quantum-inspired evolutionary algorithms(MArQ)wasproposed MArQ is a hybrid algorithm combiningQIEA with local search techniques.In MArQ,QIEAwas used to explore the whole solution space and tabusearch was employed to exploit the neighboringdomains of the searched best solutions.Several benchcomplex functions and an application example ofreactive power optimization in power systems wereapplied to test the MArQ performances.Experimentalresults show that MArQ is superior to the real-observation quantum-inspired evolutionary algorithmand several optimization algorithms reported,in termsof search capability and stability.

作者: Hongwen Liu Gexiang Zhang Chunxiu Liu Chun Fang

作者单位: School of Electrical Engineering,Southwest Jiaotong University Chengdu 610031 Sichuan,P.R.China

会议类型: 国际会议

会议名称: 2008 3rd International Conference on Intelligent System and Knowledge Engineering(第三届智能系统与知识工程国际会议)(ISKE 2008)

会议地点: 厦门

会议语种:英文

页码: 486-490

在线出版日期: 2008-11-17（万方平台首次上网日期，不代表论文的发表时间）