An improved multiple populations quantum genetic algorithm

Abstract With the in-depth study of quantum genetic algorithm (QGA), the defect of premature convergence limits its development more and more. In order to further improve QGA, we propose an improved QGA based on multi population (IQGA). In the process of population initialization in IQGA, we generat...

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Bibliographic Details
Published in:Laser physics letters 2022-09, Vol.19 (9), p.95203
Main Authors: Niu, Xu-Feng, Ma, Wen-Ping
Format: Article
Language:English
Subjects:
catastrophe strategy
genetic algorithm
multiple populations
quantum computation
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Summary:Abstract With the in-depth study of quantum genetic algorithm (QGA), the defect of premature convergence limits its development more and more. In order to further improve QGA, we propose an improved QGA based on multi population (IQGA). In the process of population initialization in IQGA, we generate multiple populations to avoid a single population falling into a local optimal value. We also abandon the fixed angle used by the traditional quantum revolving gate, and design a strategy to adjust the angle adaptively according to the difference from the optimal solution. In addition, we introduce a population catastrophe strategy to deal with the premature convergence of each population. The populations are connected based on migration operation, and the optimal solution of each population obtained by each iteration is collected in the elite group. A series of simulation experiments show that our improvement strategies of IQGA are effective.
ISSN:1612-2011
1612-202X
DOI:10.1088/1612-202X/ac8281