QUasi-Affine TRansformation Evolutionary (QUATRE) algorithm: A cooperative swarm based algorithm for global optimization

被引:135
|
作者
Meng, Zhenyu [1 ]
Pan, Jeng-Shyang [1 ,2 ]
Xu, Huarong [3 ]
机构
[1] Harbin Inst Technol, Shenzhen Grad Sch Comp Sci & Technol, HIT Campus Shenzhen Univ Town, Shenzhen, Peoples R China
[2] Fujian Univ Technol, Coll Informat Sci & Engn, Fuzhou, Peoples R China
[3] Xiamen Univ Technol, Dept Comp Sci & Technol, Xiamen, Peoples R China
基金
中国国家自然科学基金;
关键词
Benchmark functions; Large scale optimization; Particle swarm optimization; QUATRE; Real parameter optimization; State-of-the-art; PARTICLE SWARM; DIFFERENTIAL EVOLUTION;
D O I
10.1016/j.knosys.2016.06.029
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a new novel evolutionary approach named Quasi-Affine TRansformation Evolutionary (QUATRE) algorithm, which is a swarm based algorithm and use quasi-affine transformation approach for evolution. The paper also discusses the relation between QUATRE algorithm and other kinds of swarm based algorithms including Particle Swarm Optimization (PSO) variants and Differential Evolution (DE) variants. Comparisons and contrasts are made among the proposed QUATRE algorithm, state-of-the-art PSO variants and DE variants under CEC2013 test suite on real-parameter optimization and CEC2008 test suite on large-scale optimization. Experiment results show that our algorithm outperforms the other algorithms not only on real-parameter optimization but also on large-scale optimization. Moreover, our algorithm has a much more cooperative property that to some extent it can reduce the time complexity (better performance can be achieved by reducing number of generations required for a target optimum by increasing particle population size with the total number of function evaluations unchanged). In general, the proposed algorithm has excellent performance not only on uni-modal functions, but also on multi-modal functions even on higher dimension optimization problems. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:104 / 121
页数:18
相关论文
共 50 条
  • [41] A cooperative co-evolutionary particle swarm optimization algorithm based on niche sharing scheme for function optimization
    Chen Q.
    Binjiao
    Yan S.
    Advances in Intelligent and Soft Computing, 2011, 105 : 339 - 345
  • [42] A Cooperative Co-evolutionary Particle Swarm Optimization Algorithm Based on Niche Sharing Scheme for Function Optimization
    Chen, Qunxian
    BinJiao
    Yan, Shaobin
    ADVANCES IN COMPUTER SCIENCE, INTELLIGENT SYSTEM AND ENVIRONMENT, VOL 2, 2011, 105 : 339 - +
  • [43] Fast Joint Optimization of Well Placement and Control Strategy Based on Prior Experience and Quasi-Affine Transformation
    Wang, Haochen
    Zhang, Kai
    Liu, Chengcheng
    Zhang, Liming
    APPLIED SCIENCES-BASEL, 2024, 14 (18):
  • [44] ESCA: A New Evolutionary-Swarm Cooperative Algorithm
    Lung, Rodica Ioana
    Dumitrescu, D.
    NATURE INSPIRED COOPERATIVE STRATEGIES FOR OPTIMIZATION (NICSO 2007), 2008, 129 : 105 - 114
  • [45] A global particle swarm optimization algorithm
    Gao, Li-Qun
    Li, Ruo-Ping
    Zou, De-Xuan
    Dongbei Daxue Xuebao/Journal of Northeastern University, 2011, 32 (11): : 1538 - 1541
  • [46] A novel hybrid algorithm based on arithmetic optimization algorithm and particle swarm optimization for global optimization problems
    Xuzhen Deng
    Dengxu He
    Liangdong Qu
    The Journal of Supercomputing, 2024, 80 : 8857 - 8897
  • [47] A novel hybrid algorithm based on arithmetic optimization algorithm and particle swarm optimization for global optimization problems
    Deng, Xuzhen
    He, Dengxu
    Qu, Liangdong
    JOURNAL OF SUPERCOMPUTING, 2024, 80 (07): : 8857 - 8897
  • [48] Tuna Swarm Optimization: A Novel Swarm-Based Metaheuristic Algorithm for Global Optimization
    Xie, Lei
    Han, Tong
    Zhou, Huan
    Zhang, Zhuo-Ran
    Han, Bo
    Tang, Andi
    Computational Intelligence and Neuroscience, 2021, 2021
  • [49] A hybrid co-evolutionary cultural algorithm based on particle swarm optimization for solving global optimization problems
    Sun, Yang
    Zhang, Lingbo
    Gu, Xingsheng
    NEUROCOMPUTING, 2012, 98 : 76 - 89
  • [50] Tuna Swarm Optimization: A Novel Swarm-Based Metaheuristic Algorithm for Global Optimization
    Xie, Lei
    Han, Tong
    Zhou, Huan
    Zhang, Zhuo-Ran
    Han, Bo
    Tang, Andi
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2021, 2021