A Strategy Pool Adaptive Artificial Bee Colony Algorithm for Dynamic Environment through Multi-population Approach

被引:0
|
作者
Bose, Digbalay [1 ]
Biswas, Subhodip [1 ]
Kundu, Souvik [1 ]
Das, Swagatam [2 ]
机构
[1] Jadavpur Univ, Dept Elect & Commun Engn, Kolkata 700032, India
[2] Indian Stat Inst, Kolkata 700108, India
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Swarm Intelligence is based on developing metaheuristics that are modeled on certain life-sustaining principles exhibited by the biotic components of the ecosystem. There has been a surge in interest for nature inspired computing for devising more efficient models that can find solution to real-world problems using minimal resources at disposal. In this paper, an enhanced version of Artificial Bee Colony algorithm have been proposed that takes on the task of finding the optimal solution in a continuously changing (dynamic) solution space by incorporating a pool of varied perturbation strategies that operate on a multi-population group and synergizing the strategy pool with a set of diversity-inclusion techniques that help to maintain population diversity.
引用
收藏
页码:611 / 619
页数:9
相关论文
共 50 条
  • [1] Dynamic multi-population artificial bee colony algorithm
    Zhou, Xinyu
    Ling, Yiwen
    Zhong, Maosheng
    Wang, Mingwen
    2019 IEEE 31ST INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2019), 2019, : 784 - 791
  • [2] Artificial bee colony algorithm with dynamic multi-population
    Zhang, Ming
    Ji, Zhicheng
    Wang, Yan
    MODERN PHYSICS LETTERS B, 2017, 31 (19-21):
  • [3] An adaptive multi-population artificial bee colony algorithm for dynamic optimisation problems
    Nseef, Shams K.
    Abdullah, Salwani
    Turky, Ayad
    Kendall, Graham
    KNOWLEDGE-BASED SYSTEMS, 2016, 104 : 14 - 23
  • [4] Adaptive multi-population artificial bee colony algorithm based on fitness landscape analysis
    Zhou, Xinyu
    Zhang, Xiaocui
    Gao, Weifeng
    Wang, Hui
    Ma, Yong
    APPLIED SOFT COMPUTING, 2024, 164
  • [5] Adaptive multi-population artificial bee colony algorithm for wireless sensor network coverage optimisation
    Wu J.
    Wang S.
    Wei Z.
    Liu J.
    Wang H.
    International Journal of Wireless and Mobile Computing, 2023, 25 (04) : 391 - 396
  • [6] Multi-population artificial bee colony algorithm based on the nearest neighbour partition
    Ma, Mingze
    Wang, Wenjun
    Li, Xin
    INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS, 2023, 18 (03) : 235 - 244
  • [7] An Adaptive Multi-population Artificial Bee Colony Algorithm for Multi-objective Flexible Job Shop Scheduling Problem
    Cao, Yang
    Shi, Haibo
    PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 3822 - 3827
  • [8] Multi-population Based Search Strategy Ensemble Artificial Bee Colony Algorithm with a Novel Resource Allocation Mechanism
    Wu, Liu
    Sun, Zhiwei
    Zhang, Kai
    Li, Genghui
    Wang, Ping
    NEURAL INFORMATION PROCESSING (ICONIP 2017), PT IV, 2017, 10637 : 336 - 345
  • [9] Training of artificial neural networks with the multi-population based artifical bee colony algorithm
    Kirankaya, Cihat
    Aykut, Latife Gorkemli
    NETWORK-COMPUTATION IN NEURAL SYSTEMS, 2022, 33 (1-2) : 124 - 142
  • [10] 3 Migrating Forager Population in a Multi-population Artificial Bee Colony Algorithm with Modified Perturbation Schemes
    Biswas, Subhodip
    Kundu, Souvik
    Bose, Digbalay
    Das, Swagatam
    Suganthan, P. N.
    Panigrahi, B. K.
    2013 IEEE SYMPOSIUM ON SWARM INTELLIGENCE (SIS), 2013, : 248 - 255