摘要
量子遗传算法(QGA)是量子计算和遗传算法相结合的产物,将量子的态矢量表示引入到遗传算法中,具有比遗传算法更好的搜索效率和收敛性。本文首先介绍了量子遗传算法的基本原理,讨论了基于量子遗传算法的一系列改进,然后将量子遗传算法应用于无约束优化问题,实例计算表明了算法在该类问题中的有效性和可行性。
Quantum genetic algorithm is a product which is combined quantum computation with genetic algorithm; the state vector representation is introduced to the genetic algorithm. Comparing to the genetic algorithm, it has good inquring efficiency and convergence, This paper introduces the principle of quantum genetic algorithm,and discusses on the reforms of the algorithm;then it uses the algorithm in the non-restriction optimization. Some practical examples show the algorithm is effective and feasible.
出处
《信息技术》
2005年第10期34-37,119,共5页
Information Technology
关键词
遗传算法
量子遗传算法
多宇宙并行量子遗传算法
无约束优化问题
genetic algorithm
quantum genetic algorithm
multi- cosmos parallel quantum genetic algorithm
non- restriction optimization
