A quantum-inspired evolutionary algorithm for global optimizations of inverse problems

作者：Yang, Wenjia; Zhou, Haijuan; Li, Yuling^*

来源：COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2014, 33(1-2): 201-209.

DOI：10.1108/COMPEL-11-2012-0333

• Inverse problem
• Evolutionary algorithm
• Quantum computing

Purpose - The purpose of this paper is to report the investigations on the potential of a new evolutionary algorithm based on probabilistic models the quantum-inspired evolutionary algorithm (QEA) in solving inverse problems. @@@ Design/methodology/approach - An improved QEA. @@@ Findings - The proposed algorithm is an efficient and robust global optimizer for solving inverse Problems. @@@ Originality/value - To enhance the convergence speed without compromising the diversity performances of the populations, a new definition of global information sharing is introduced and implemented. To guarantee the balance between exploration and exploitation searches, a different migration strategy and formula, as well as a novel formulation for adaptively updating the rotation angle, are developed.

• 出版日期2014
• 单位浙江大学