计算机科学

计算机科学 ›› 2025, Vol. 52 ›› Issue (10): 190-200.doi: 10.11896/jsjkx.250500127

• 人工智能 • 上一篇    下一篇

量子元启发式算法及其应用综述

阮宁1, 李淳1, 马昊月2, 贾异3, 李涛2   

  1. 1 河南师范大学软件学院 河南 新乡 453007
    2 河南师范大学计算机与信息工程学院 河南 新乡 453007
    3 国家自然科学基金委员会高技术研究发展中心 北京 100006
  • 收稿日期:2025-05-27 修回日期:2025-09-11 出版日期:2025-10-15 发布日期:2025-10-14
  • 通讯作者: 李涛(litao0116@163.com)
  • 作者简介:(ruanning@htu.edu.cn)
  • 基金资助:
    国家自然科学基金(62406104);河南省科技攻关项目(252102211012);河南省高等学校重点科研项目(25A520029);河南省高等学校青年骨干教师培养计划(2025GGJS033)

Review of Quantum-inspired Metaheuristic Algorithms and Its Applications

RUAN Ning1, LI Chun1, MA Haoyue2, JIA Yi3, LI Tao2   

  1. 1 School of Software,Henan Normal University,Xinxiang,Henan 453007,China
    2 School of Computer and Information Engineering,Henan Normal University,Xinxiang,Henan 453007,China
    3 National Natural Science Foundation of China,High Tech Research and Development Center,Beijing 100006,China
  • Received:2025-05-27 Revised:2025-09-11 Online:2025-10-15 Published:2025-10-14
  • About author:RUAN Ning,born in 1988,postgra-duate,lecturer,is a member of CCF(No.W0391M).His main research interests include evolutionary computing,graph machine learning and data mi-ning.
    LI Tao,born in 1990,Ph.D,associate professor,is a member of CCF(No.F5541M).His main research interests include evolutionary computing and machine learning.
  • Supported by:
    National Natural Science Foundation of China(62406104),Key Scientific and Technological Project of Henan Province(252102211012),Key Research Project Plan for Higher Education Institutions in Henan Province(25A520029) and Training Program for Young Backbone Teachers in Higher Education Institutions of Henan Province(2025GGJS033).

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摘要： 量子元启发式算法是将量子计算应用到元启发式算法中而开发出来的。该类算法擅于求解组合和数值优化问题,具有加速收敛、增强探索和开发能力等特点,且能获得比传统元启发式算法更高的性能结果。文中主要概述和回顾量子元启发式算法的理论方法及其应用。首先对量子计算的基本概念和计算原理进行阐述,并分析目前量子计算领域亟需解决的挑战性问题;然后阐述6种经典量子元启发式算法运行的基本原理,分析最新的研究进展,概括它们在求解特定领域问题的优劣势,并展示量子元启发式算法在不同学科及工程场景中的应用;最后对量子元启发式算法理论方法存在的问题进行剖析与探讨,并总结未来量子元启发式算法理论和应用发展方向。

关键词: 量子计算, 元启发式算法, 进化计算, 全局最优, 智能优化

Abstract: The quantum meta heuristic algorithm is developed by applying quantum computing to the meta-heuristic algorithm.This kind of algorithm is good at solving combinatorial and numerical optimization problems,and has the characteristics of acce-lerated convergence,enhanced exploration and development capabilities,and can obtain higher performance results than traditional meta-heuristic algorithms.This paper mainly summarizes and reviews the theoretical methods and applications of quantum meta-heuristic algorithms.Firstly,this paper expounds the basic concepts and principles of quantum computing,and analyzes the challenging problems that need to be solved urgently in the field of quantum computing.Then,this paper expounds the basic principles of six classical quantum meta-heuristic algorithms,analyzes the latest research progress,gives their advantages and disadvantages in solving domain-specific problems,and demonstrates the application of quantum meta-heuristic algorithms in different disciplines and engineering scenarios.Finally,this paper analyzes and explores the existing problems in the theories and methods of quantum meta-heuristic algorithms,and summarizes the future development direction of the theory and application of quantum meta-heuristic algorithms.

Key words: Quantum computing,Metaheuristics algorithm,Evolutionary computing,Global optimum,Intelligent optimization

中图分类号: 

  • TP391
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