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Received:December 19, 2016
Received:December 19, 2016
中文摘要: 为提高布谷鸟搜索算法的寻优能力,通过在经典布谷鸟搜索算法中引入量子计算机制,提出了一种量子衍生布谷鸟搜索算法.该算法采用量子比特编码个体,采用泡利矩阵确定旋转轴,采用Levy飞行原理确定旋转角度,采用量子比特在Bloch球面上的绕轴旋转实现个体更新.标准函数极值优化的实验结果表明,与传统布谷鸟搜索算法相比,该算法的搜索能力确有明显提升.
Abstract:In order to improve the search ability of the cuckoo search algorithm, this paper proposes a quantum-inspired cuckoo search algorithm by introducing the quantum computing mechanism into the classical cuckoo search algorithm.. In the proposed algorithm, the qubits are used to encode individuals, and the Pauli matrixes are employed to determine rotation axis. The Levy flight principle is applied to obtain rotation angle, and the rotation of the qubits on the Bloch sphere is used to update the individuals. The experimental results of extreme optimization of benchmark test functions show that the proposed algorithm is obviously superior to the classical cuckoo search algorithm in optimization ability.
keywords: bionic intelligent optimization swarm intelligence optimization cuckoo algorithm quantum-inspired optimization algorithm design
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基金项目:黑龙江省教育厅科学技术研究项目(12541059)
引用文本:
李盼池,杨淑云,刘显德,潘俊辉,肖红,曹茂俊.量子衍生布谷鸟搜索算法.计算机系统应用,2017,26(9):122-127
LI Pan-Chi,YANG Shu-Yun,LIU Xian-De,PAN Jun-Hui,XIAO Hong,CAO Mao-Jun.Quantum-Inspired Cuckoo Search Algorithm.COMPUTER SYSTEMS APPLICATIONS,2017,26(9):122-127
李盼池,杨淑云,刘显德,潘俊辉,肖红,曹茂俊.量子衍生布谷鸟搜索算法.计算机系统应用,2017,26(9):122-127
LI Pan-Chi,YANG Shu-Yun,LIU Xian-De,PAN Jun-Hui,XIAO Hong,CAO Mao-Jun.Quantum-Inspired Cuckoo Search Algorithm.COMPUTER SYSTEMS APPLICATIONS,2017,26(9):122-127