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Hybrid quantum genetic algorithms and performance analysis

  • Ling Wang*
  • , Hao Wu
  • , Fang Tang
  • , Da Zhong Zheng
  • , Yi Hui Jin
  • *此作品的通讯作者
  • Tsinghua University

科研成果: 期刊稿件文章同行评审

摘要

Quantum algorithm (QA) with updating of quantum gates and catastrophe of population is compared with quantum genetic algorithm (QGA) by including crossover and mutation for quantum bits. Furthermore, a framework of hybrid quantum GA is proposed which combines the quantum based search and classic genetic search, and hybrid QGA with binary encoding (BQGA) and hybrid QGA with real encoding (RQGA) are presented. Numerical simulation on typical problems shows that the performances of RQGA are the best among all testing algorithms and it is much robust on parameters and initial conditions.

源语言英语
页(从-至)156-160
页数5
期刊Kongzhi yu Juece/Control and Decision
20
2
出版状态已出版 - 2月 2005

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