杨玉, 戴红伟, 李存华. 量子干扰交叉遗传算法及其应用研究[J]. 微电子学与计算机, 2012, 29(3): 26-30.
引用本文: 杨玉, 戴红伟, 李存华. 量子干扰交叉遗传算法及其应用研究[J]. 微电子学与计算机, 2012, 29(3): 26-30.
YANG Yu, DAI Hong-wei, LI Cun-hua. Quantum Interference Crossover Based GA and its Application[J]. Microelectronics & Computer, 2012, 29(3): 26-30.
Citation: YANG Yu, DAI Hong-wei, LI Cun-hua. Quantum Interference Crossover Based GA and its Application[J]. Microelectronics & Computer, 2012, 29(3): 26-30.

量子干扰交叉遗传算法及其应用研究

Quantum Interference Crossover Based GA and its Application

  • 摘要: 针对遗传算法中传统交叉算子交叉效率低下等缺点, 提出改进型全干扰量子交叉遗传算法.与基于位置信息的经典量子全干扰交叉模型不同, 改进型交叉算子通过距离比较, 能够获取质量更高的候选解.通过对旅行商问题 (TSP) 求解的对比实验表明, 改进量子交叉遗传算法能有效平衡全局搜索和局部探索, 具有更强的稳定性和寻优能力.

     

    Abstract: In order to overcome the low efficiency of crossover in Genetic Algorithm (GA), a modified quantum interference crossover based GA was proposed.Unlike position based classical quantum interference crossover, the improved crossover can generate better solutions through distance comparison.Simulation results on Traveling Salesman Problem (TSP) show that the new algorithm can well balance the exploration and exploitation abilities in the whole searching space, and have superior ability of searching the global optimal of near-optimal solutions.

     

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