文章詳目資料

Journal of Computers EIMEDLINEScopus

  • 加入收藏
  • 下載文章
篇名 Hybrid Quantum Particle Swarm Algorithm Based on Lévy Flights
卷期 31:3
作者 Qi-Wen Zhang 、 Song-Qi Hu
頁次 058-071
關鍵字 global convergence 、 Lévy flights 、 population diversity 、 quantum computation 、 quantum particle swarm algorithm 、 EI 、 MEDLINE 、 Scopus
出刊日期 202006
DOI 10.3966/199115992020063103005

中文摘要

英文摘要

In order to diversify the particle swarm during the searching process of quantum particle swarm optimization (QPSO) and avoid the algorithm being trapped into premature easily, a hybrid quantum particle swarm optimization algorithm based on Lévy flights is proposed in this paper. The new algorithm effectively takes advantage of quantum computing and Lévy flights. We use the probability amplitude encoding method of the quantum bit to initialize the particle position and combine the potential well particle updating formula with the quantum rotation gate to update the particle swarm, which effectively ameliorates the search process and increases the population diversity. Then the Lévy flights strategy is employed to improve the population variation process and enhance the quality of the solution while preventing the algorithm from falling into the precocious convergence. Compared with other algorithms on benchmark functions, it is shown that the algorithm is effective and feasible.

本卷期文章目次

查看更多

關鍵知識WIKI

查看更多

相關文獻