非线性混沌网络系统的分散性能量子优化算法  

Quantum Optimization Algorithm for Decentralized Performance of Nonlinear Chaotic Network Systems

作　　者：王晓晗[1] WANG Xiaohan(School of Mathematies and Infommation Science,Xianyang Normal University,Xianyang 712000,China)

机构地区：[1]咸阳师范学院数学与信息科学学院,陕西咸阳712000

出　　处：《吉林大学学报（信息科学版）》2022年第3期424-430,共7页Journal of Jilin University（Information Science Edition）

基　　金：陕西省教育科学“十三五”规划基金资助项目(SGH20Y1242);咸阳师范学院教育教学改革研究基金资助项目(201402025,2019Y038)。

摘　　要：针对量子优化算法应用时,优化控制方法的差异会造成优化算法收敛时间过长的问题,提出非线性混沌网络系统的分散性能量子优化算法。采用分段Logistic混沌映射方法,获取量子初始化位置。依托于适应度划分量子种群,分别针对顶层和底层种群建立相应进化模式。利用多个非线性连续时间子系统,设计非线性混沌优化控制方法,确定最佳控制方案。最后,引入早熟收敛判断机制得到最优解计算结果。实验结果表明,与传统方法相比,所提优化算法收敛时间明显减少。When quantum optimization algorithm is applied, the difference of optimization control methods will cause the convergence time of optimization algorithm to be too long. Therefore, a quantum optimization algorithm for decentralized performance of nonlinear chaotic network systems is proposed. The piecewise Logistic chaotic mapping method is used to obtain the quantum initialization position. Based on the fitness division of quantum populations, the corresponding evolutionary models are established for the top and bottom populations respectively. Using multiple nonlinear continuous time subsystems, the nonlinear chaos optimal control method is designed and the optimal control scheme is determined. Finally, the premature convergence judgment mechanism is introduced to obtain the calculation results of the optimal solution. Experimental results show that the convergence time of the proposed optimization algorithm is significantly reduced compared to the traditional method.

关 键 词：非线性混沌网络系统 分散 量子优化 混沌初始化 停滞性 优化控制 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]