基于量子自由粒子模型的优化算法框架  

Optimization Algorithm Framework Based on Quantum Free Particle Model

作　　者：王鹏[1] 杨云亭 WANG Peng;YANG Yun-ting(School of Computer Science and Technology,Southwest Minzu University,Chengdu,Sichuan 610225,China;Chengdu Institute of Computer Application,Chinese Academy of Sciences,Chengdu,Sichuan 610041,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]西南民族大学计算机科学与技术学院,四川成都610225 [2]中国科学院成都计算机应用研究所,四川成都610041 [3]中国科学院大学,北京100049

出　　处：《电子学报》2020年第7期1348-1354,共7页Acta Electronica Sinica

基　　金：国家自然科学基金(No.60702075);西南民族大学中央高校基本科研业务费专项资金(No.2019NYB22)。

摘　　要：基于量子系统下的自由粒子模型,提出了多尺度自由粒子优化算法(Multi-scale Free Particle Optimization Algorithm,MFPOA),并在物理模型的基础之上研究了该算法的内部机制.通过类比量子系统和优化系统,将优化问题的求解过程转化成粒子在微观系统下的运动过程.通过在MATLAB仿真平台上对自由粒子优化算法的参数设置进行了研究,并分析了与同类搜索机制的算法的区别.最后通过实验得出,MFPOA更适合求解单模简单函数,求解复杂多模函数需要更多的迭代次数.Based on the free particle model of quantum system,the Multi-scale Free Particle Optimization Algorithm(MFPOA)is proposed,and the internal mechanism of the algorithm is studied on the basis of the physical model.Through analogy between quantum system and optimization system,the solving process of optimization problem is transformed into the motion process of particles under the microscopic system.The parameter setting of free particle optimization is studied on MATLAB simulation platform,and the differences between the algorithm and similar search mechanism are analyzed.Finally,experiments show that MFPOA is more suitable for solving single-mode functions,and more iterations are needed to solve complex multi-mode functions.

关 键 词：自由粒子 谐振子 均匀分布采样 高斯采样 波函数 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]