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基于Bloch球面搜索的量子鱼群算法

ISSN号：1002-0411
期刊名称：信息与控制
时间：2014.6
页码：647-653
分类：TP18[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程]
作者机构：[1]东北石油大学招生就业处,黑龙江大庆163318, [2]中国石油物资公司,北京100029, [3]东北石油大学计算机与信息技术学院,黑龙江大庆163318
相关基金：国家自然科学基金资助项目（61170132）;黑龙江省教育厅科学技术研究项目（12541059）
相关项目：量子过程神经网络模型及算法研究

关键词：量子计算, 鱼群优化, Bloch球面搜索, 算法设计, quantum computing , fish swarm optimizing , Bloch sphere search, algorithm design

中文摘要：

为提高智能优化算法的优化能力，提出一种在Bloch球面上建立搜索机制的新模型，将该模型与鱼群优化相融合，设计了一种量子衍生鱼群算法．在该算法中，鱼群采用基于Bloch球面描述的量子比特编码；采用向量积理论建立旋转轴，采用泡利矩阵建立旋转矩阵，采用量子比特在Bloch球面上的绕轴旋转实现鱼群的移动、跟踪、捕获、聚集；采用泡利矩阵实现量子比特测量，以获得量子比特的Bloch坐标；通过解空间变换可以获得优化问题的实际解．该方法的突出优点是能够同时调整量子比特的两个参数，并自动实现两个调整量的最佳匹配，从而可加速优化进程．实现结果表明，该方法的优化能力比普通鱼群算法具有明显提高．

英文摘要：

To enhance the performance of the intelligent optimization algorithm, we propose a new model for per- forming asearch on a Bloch sphere. Then, by integrating this model into the artificial fish swarm optimization, we present a quantum-inspired artificial fish swarm optimization algorithm. In the proposed method, the fishes are encoded with qubits described on the Bloch sphere. Vector product theory is adopted to establish the rota- tion axis, and the Pauli matrices are used to construct the rotation matrices. The four fish behaviors, moving, tracking, capturing and aggregating, are achieved by rotating the current qubit about the rotation axis towards the target qubit on the Bloch sphere. The Bloch coordinates of the qubit can be obtained by measunnent with the Pauli matrices, and the optimization solutions can be presented through the solution space transformation. The highlight advantages of this method are the ability to simultaneously adjust two parameters of a qubit and automatically achieve the best match between two adjustment quantities, which may accelerate the optimiza- tion process. The experiment results show that the proposed method obviously outperfmans the classical one in convergence speed, and achieves better levels for some benchmark functions.

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