1. 西南交通大学信息科学与技术学院,四川,成都,610031
2. 北京邮电大学电信工程学院,北京,100876
3. 西南交通大学信息科学与技术学院四川成都,610031
4. 北京邮电大学电信工程学院北京,100876
纸质出版:2007
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邢焕来, 潘炜, 邹喜华. 一种解决组合优化问题的改进型量子遗传算法[J]. 电子学报, 2007,35(10):1999-2002.
XING Huan-lai, PAN Wei, ZOU Xi-hua. A Novel Improved Quantum Genetic Algorithm for Combinatorial Optimization Problems[J]. Acta Electronica Sinica, 2007, 35(10): 1999-2002.
在量子遗传算法(QGA)的基础上
提出了一种解决组合优化问题的改进型量子遗传算法(NIQGA).为充分利用量子态的干涉性和纠缠性
该算法引入了动态调整量子门旋转角步长机制、量子交叉操作和量子变异操作
因而具有更高的搜索效率.利用两种典型组合优化问题——0/1背包问题和路由选择问题进行验证.结果表明
相比于GA和QGA
NIQGA具有收敛速度快和全局搜索能力强的特点
在解决基因间弱关联性的组合优化问题时有更优的性能.
Based on quantum genetic algorithm(QGA)
a novel improved quantum genetic algorithm(NIQGA)to solve combinatorial optimization problem is proposed.To make full use of interference and entanglement characteristics of quantum state
dynamic step length in adjustment of angle of quantum gate
quantum crossover operation and quantum mutation operation are introduced
therefore high efficiency for optimization is achieved.Two typical combinatorial optimization problems—0/1 knapsack problem and route selection problem
are adopted to confirm the performance of NIQGA.Experimental results show that compared with GA and QGA
NIQGA is characterized by fast convergence rate and excellent capability on global optimization
especially better performance for combinatorial optimization problem with less correlation of genes.
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