一种基于相位编码的量子遗传算法  

A Quantum Genetic Algorithm Based on Phase Encoding

作　　者：李盼池[1,2] 宋考平[1] 杨二龙[1] 

机构地区：[1]东北石油大学石油与天然气工程博士后科研流动站,黑龙江大庆163318 [2]东北石油大学计算机与信息技术学院,黑龙江大庆163318

出　　处：《信息与控制》2010年第6期681-685,共5页Information and Control

基　　金：国家自然科学基金资助项目(60773065);中国博士后科学基金资助项目(20090460864);黑龙江省博士后科学基金资助项目(LBHZ09289);黑龙江省教育厅科学技术研究项目(11551015)

摘　　要：基于量子位测量的二进制量子遗传算法在用于连续问题优化时,由于频繁的解码运算,严重降低了优化效率.针对这一问题,本文提出了一种基于量子位相位编码的量子遗传算法.该方法直接采用量子位的相位对染色体进行编码,采用量子旋转门实现染色体上相位的更新,采用Pauli-Z门实现染色体的变异.在该方法中,由于优化过程统一在空间[0,2π]~n进行,而与具体问题无关,因此,对不同尺度空间的优化问题具有良好的适应性.以函数极值优化为例,仿真结果表明该方法的搜索能力和优化效率明显优于普通量子遗传算法和标准遗传算法.Due to the frequent decoding operations,the efficiency of optimization is severely reduced when the binary quantum genetic algorithm based on qubits measure is applied to the continuous space optimization.To solve this problem,a quantum genetic algorithm based on phase encoding is proposed.In this method,the chromosomes are encoded by the phase of qubits,evolved by quantum rotation gates,and mutated by quantum Pauli-Z gates.The optimization process is performed in[0,2π]~n,which has nothing to do with specific issues,therefore,the proposed method has good adaptability for a variety of optimization problems.In application of function extremum optimization,the simulation results show that the approach is superior to either common quantum genetic algorithm or simple genetic algorithm in both search capability and optimization efficiency.

关 键 词：量子遗传算法 相位编码 优化算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]