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Computer Engineering ›› 2011, Vol. 37 ›› Issue (5): 199-201. doi: 10.3969/j.issn.1000-3428.2011.05.067

• Networks and Communications • Previous Articles     Next Articles

Improved Quantum Genetic Algorithm and Its Application

FENG An-hui, SU Hong-sheng   

  1. (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)
  • Online:2011-03-05 Published:2012-10-31

一种改进的量子遗传算法及其应用

封安辉,苏宏升   

  1. (兰州交通大学自动化与电气工程学院,兰州 730070)
  • 作者简介:封安辉(1981-),男,硕士,主研方向:神经网络; 苏宏升,教授

Abstract: In order to solve the problems of optimization efficiency and inferior local search of quantum genetic algorithm whose coding is based on bloch coordinates, this paper proposes two improvements, combines local search with global search which is based on comparative population, and expands the search space from one sphere to three-sphere according to the characteristics of three chains. With the application of function extreme optimization of multi-variables, simulation results show that the improved algorithm has lower generation, higher efficiency, diverse populations, and it proves that the improvement is efficient.

Key words: quantum computation, optimization algorithm, quantum genetic algorithm, function optimization

摘要: 针对基于Bloch球面坐标编码的量子遗传算法应用中的优化效率低和局部寻优较差能力问题,提出2点改进措施:在比较种群的基础上将局部搜索与全局搜索相结合;依据三链特性将搜索空间扩展为3Bloch球面空间。将改进算法应用于多变量函数极值优化问题,仿真结果表明,该改进算法寻优代数小、收敛速度快、效率高,并且具有较好的种群多样性,验证了改进措施的有效性。

关键词: 量子计算, 优化算法, 量子遗传算法, 函数优化

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