Authors: Jialin Li; Wei Li; Ying Huang; Chengtian Ouyang
Addresses: School of Science and Technology, Gannan Normal University, Ganzhou, Jiangxi Province, China ' School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi Province, China ' Key Laboratory of Jiangxi Province for Numerical Simulation and Emulation Techniques, Gannan Normal University, Ganzhou, Jiangxi Province, China ' School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi Province, China
Abstract: In this paper, quantum rotate gate is improved, which is the main operation in the population update of the traditional quantum evolutionary algorithm. A new rotation angle is defined, preventing the algorithm from easily falling into local optimum state in the middle and late term. Based on the characteristics of TSP, a modified quantum rotate gate is proposed in this paper to adaptively adjust the rotation angle, according to the evolution generations and the adapt to degree of the value to adaptive dynamic adjustment of the rotation angle, resulting a better global search capability. At the same time, in order to prevent the extramalisation of the probability amplitudes α and β falling into local optimal algorithm, this paper adopted the Hε gate on the probability amplitude of the rotation to make the corrective manipulation. The comparative experimental results showed that the algorithm's stability and accuracy have been greatly improved in solving the TSP problem, compared with the conventional quantum evolutionary algorithm.
Keywords: quantum-inspired evolutionary; quantum rotate gate; adaptive quantum rotation angle; travelling salesman problem.
International Journal of High Performance Systems Architecture, 2017 Vol.7 No.4, pp.223 - 230
Available online: 05 Jun 2018 *Full-text access for editors Access for subscribers Purchase this article Comment on this article