《计算机应用》唯一官方网站 ›› 2024, Vol. 44 ›› Issue (3): 819-830.DOI: 10.11772/j.issn.1001-9081.2023030380

• 先进计算 • 上一篇    下一篇

智能算法的亚群优化策略综述

杜晓昕(), 周薇, 王浩, 郝田茹, 王振飞, 金梅, 张剑飞   

  1. 齐齐哈尔大学 计算机与控制工程学院,黑龙江 齐齐哈尔 161006
  • 收稿日期:2023-04-11 修回日期:2023-06-06 接受日期:2023-06-08 发布日期:2023-07-12 出版日期:2024-03-10
  • 通讯作者: 杜晓昕
  • 作者简介:周薇(1999—),女,河北保定人,硕士研究生,主要研究方向:群智能优化算法
    王浩(1996—),男,河南商丘人,硕士研究生,主要研究方向:智能优化算法
    郝田茹(1998—),女,山西吕梁人,硕士研究生,主要研究方向:群智能优化算法
    王振飞(1999—),男,山东潍坊人,硕士研究生,主要研究方向:群智能优化算法
    金梅(1977—),女,辽宁鞍山人,讲师,硕士,主要研究方向:数据库、数据分析
    张剑飞(1974—),男,黑龙江齐齐哈尔人,教授,博士,主要研究方向:深度学习。
  • 基金资助:
    黑龙江省省属高等学校基本科研业务费自然科学类青年创新人才项目(145209206)

Survey of subgroup optimization strategies for intelligent algorithms

Xiaoxin DU(), Wei ZHOU, Hao WANG, Tianru HAO, Zhenfei WANG, Mei JIN, Jianfei ZHANG   

  1. School of Computer and Control Engineering,Qiqihar University,Qiqihar Heilongjiang 161006,China
  • Received:2023-04-11 Revised:2023-06-06 Accepted:2023-06-08 Online:2023-07-12 Published:2024-03-10
  • Contact: Xiaoxin DU
  • About author:ZHOU Wei, born in 1999, M. S. candidate. Her research interests include swarm intelligent optimization algorithm.
    WANG Hao, born in 1996, M. S. candidate. His research interests include swarm intelligent optimization algorithm.
    HAO Tianru, born in 1998, M. S. candidate. Her research interests include swarm intelligent optimization algorithm.
    WANG Zhenfei, born in 1999, M. S. candidate. His research interests include swarm intelligent optimization algorithm.
    JIN Mei, born in 1977, M. S., lecturer. Her research interests include database, data analysis.
    ZHANG Jianfei, born in 1974, Ph. D., professor. His research interests include deep learning.
  • Supported by:
    Natural Science Young Innovative Talent Project in Basic Scientific Research Funds for Colleges and Universities of Heilongjiang Province(145209206)

摘要:

群智能算法的优化是提升群智能算法性能的一个主要途径,随着群智能算法越来越广泛地运用到各类模型优化、生产调度、路径规划等问题中,对智能算法性能的要求也越来越高。亚群策略作为一种优化群智能算法的重要手段,能够灵活地平衡算法的全局勘探能力和局部开发能力,已经成为群智能算法的研究热点之一。为了促进亚群优化策略的发展和应用,对动态亚群策略、基于主从范式的亚群策略和基于网络结构的亚群策略进行了详细调查,阐述了各类亚群策略的结构特点、改进方式和应用场景。最后,总结了亚群策略目前存在的问题以及未来的研究趋势和发展方向。

关键词: 粒子群优化算法, 群智能算法, 动态亚群策略, 主从范式, 网络结构

Abstract:

The optimization of swarm intelligence algorithms is a main way to improve swarm intelligence algorithms. As the swarm intelligence algorithms are more and more widely used in all kinds of model optimization, production scheduling, path planning and other problems, the demand for performance of intelligent algorithms is also getting higher and higher. As an important means to optimize swarm intelligence algorithms, subgroup strategies can balance the global exploration ability and local exploitation ability flexibly, and has become one of the research hotspots of swarm intelligence algorithms. In order to promote the development and application of subgroup strategies, the dynamic subgroup strategy, the subgroup strategy based on master-slave paradigm, and the subgroup strategy based on network structure were investigated in detail. The structural characteristics, improvement methods and application scenarios of various subgroup strategies were expounded. Finally, the current problems and the future research trends and development directions of the subgroup strategies were summarized.

Key words: Particle Swarm Optimization (PSO) algorithm, swarm intelligence algorithm, dynamic subgroup strategy, master-slave paradigm, network structure

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