A quantum-inspired evolutionary algorithm for global optimizations of inverse problems
ISSN: 0332-1649
Article publication date: 1 January 2014
Abstract
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.
Keywords
Citation
Yang, W., Zhou, H. and Li, Y. (2014), "A quantum-inspired evolutionary algorithm for global optimizations of inverse problems", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 33 No. 1/2, pp. 201-209. https://doi.org/10.1108/COMPEL-11-2012-0333
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited