title: An Allele Real-Coded Quantum Evolutionary Algorithm Based on Hybrid Updating Strategy.
abstract: For improving convergence rate and preventing prematurity in quantum evolutionary algorithm, an allele real-coded quantum evolutionary algorithm based on hybrid updating strategy is presented. The real variables are coded with probability superposition of allele. A hybrid updating strategy balancing the global search and local search is presented in which the superior allele is defined. On the basis of superior allele and inferior allele, a guided evolutionary process as well as updating allele with variable scale contraction is adopted. And H ε gate is introduced to prevent prematurity. Furthermore, the global convergence of proposed algorithm is proved by Markov chain. Finally, the proposed algorithm is compared with genetic algorithm, quantum evolutionary algorithm, and double chains quantum genetic algorithm in solving continuous optimization problem, and the experimental results verify the advantages on convergence rate and search accuracy.
authors.affiliation: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China.
authors.forename: Yu-Xian
authors.initials: YX
authors.lastname: Zhang
authors.affiliation: School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, China.
authors.forename: Xiao-Yi
authors.initials: XY
authors.lastname: Qian
authors.affiliation: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China.
authors.forename: Hui-Deng
authors.initials: HD
authors.lastname: Peng
authors.affiliation: College of Information Science and Engineering, Northeastern University, Shenyang 110004, China.
authors.forename: Jian-Hui
authors.initials: JH
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D011789:Quantum Theory