Particle swarm optimisation for dynamic optimisation problems: a review

被引：54
|
作者：
Jordehi, Ahmad Rezaee [1 ]
机构：
[1] Univ Putra Malaysia, Dept Elect Engn, Serdang 43400, Malaysia
来源：
NEURAL COMPUTING & APPLICATIONS | 2014年 / 25卷 / 7-8期
关键词：
Particle swarm optimisation; Optimisation; Dynamic optimisation problem; ALGORITHM; OPTIMA; STRATEGY; SYSTEM; MODEL; PSO;
D O I：
10.1007/s00521-014-1661-6
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Some real-world optimisation problems are dynamic; that is, their objective function and/or constraints vary over time. Solving such problems is very challenging. Particle swarm optimisation (PSO) is a well-known and efficient optimisation algorithm. In this paper, the PSO variants, devised for dynamic optimisation problems, are reviewed. This is the first comprehensive review that is conducted on PSO variants in dynamic environments. The author believes that this paper can be useful for researchers who intend to solve dynamic optimisation problems.
引用
收藏
页码：1507 / 1516
页数：10
相关论文
共 50 条
  • [41] Hybrid Particle Swarm Optimisation for Data Clustering
    Teng, Sing Loong
    Chan, Chee Seng
    Lim, Mei Kuan
    Lai, Weng Kin
    SECOND INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING, 2010, 7546
  • [42] Particle swarm optimisation strategies for IOL formula constant optimisation
    Langenbucher, Achim
    Szentmary, Nora
    Cayless, Alan
    Wendelstein, Jascha
    Hoffmann, Peter
    ACTA OPHTHALMOLOGICA, 2023, 101 (07) : 775 - 782
  • [43] Particle swarm optimisation with time varying cognitive avoidance component
    Biswas, Anupam
    Biswas, Bhaskar
    Kumar, Anoj
    Mishra, K. K.
    INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING, 2018, 16 (01) : 27 - 41
  • [44] Optimised implementation of AVR system using particle swarm optimisation
    Jarrah, Amin
    Zaitoun, Mohmmad
    INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING, 2022, 25 (03) : 272 - 284
  • [45] Application of particle swarm optimisation algorithm in manipulator compliance control
    Guo, Kai
    Bai, Zhi
    Ma, Zhilin
    INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS, 2023, 18 (02) : 113 - 127
  • [46] Hard Deterministic Particle Swarm Optimisation for Certain Result Solution
    Thongkrairat, Somsin
    Chutchavong, Vanvisa
    2021 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC), 2021,
  • [47] Particle swarm optimisation with grey wolf optimisation for optimal container resource allocation in cloud
    Vhatkar, Kapil Netaji
    Bhole, Girish P.
    IET NETWORKS, 2020, 9 (04) : 189 - 199
  • [48] Deep learning-driven particle swarm optimisation for additive manufacturing energy optimisation
    Qin, Jian
    Liu, Ying
    Grosvenor, Roger
    Lacan, Franck
    Jiang, Zhigang
    JOURNAL OF CLEANER PRODUCTION, 2020, 245
  • [49] A multi-objective particle swarm optimisation for filter-based feature selection in classification problems
    Xue, Bing
    Cervante, Liam
    Shang, Lin
    Browne, Will N.
    Zhang, Mengjie
    CONNECTION SCIENCE, 2012, 24 (2-3) : 91 - 116
  • [50] Multi-objective optimisation of traffic signal control based on particle swarm optimisation
    Jian, Li
    INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING, 2020, 11 (04) : 547 - 553
12345