Optimization Algorithm Framework Based on Quantum Free Particle Model

doi:10.3969/j.issn.0372-2112.2020.07.013

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Optimization Algorithm Framework Based on Quantum Free Particle Model

更新时间：2025-07-08

- Optimization Algorithm Framework Based on Quantum Free Particle Model
- Acta Electronica Sinica Vol. 48, Issue 7, Pages: 1348-1354(2020)
- 作者机构：
  
  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
  4. 西南民族大学计算机科学与技术学院,四川,成都,610225
  5. 中国科学院成都计算机应用研究所,四川,成都,610041
  6. 中国科学院大学,北京,100049
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.60702075);Fundamental Research Funds for the Central Universities of Southwest Minzu University (No.2019NYB22)
- DOI：10.3969/j.issn.0372-2112.2020.07.013
  CLC： TP301.6
- Published Online：25 July 2020，
  
  Published：2020
- 稿件说明：
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Optimization Algorithm Framework Based on Quantum Free Particle Model[J]. Acta Electronica Sinica, 2020, 48(7): 1348-1354.
DOI：

Optimization Algorithm Framework Based on Quantum Free Particle Model[J]. Acta Electronica Sinica, 2020, 48(7): 1348-1354. DOI： 10.3969/j.issn.0372-2112.2020.07.013.

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.

Abstract

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.

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