JADE: adaptive differential evolution with a small population

被引:24
|
作者
Brown, Craig [1 ]
Jin, Yaochu [2 ]
Leach, Matthew [3 ]
Hodgson, Martin [1 ]
机构
[1] Bosch Thermotechnol Ltd, Worcester WR4 9SW, Worcs, England
[2] Univ Surrey, Dept Comp, Guildford GU2 7XH, Surrey, England
[3] Univ Surrey, Fac Engn & Phys Sci, Ctr Environm Strategy, Guildford GU2 7XH, Surrey, England
基金
英国工程与自然科学研究理事会;
关键词
Micro differential evolution; Small population; External archive; JADE; OPTIMIZATION; ALGORITHM; SIZE;
D O I
10.1007/s00500-015-1746-x
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 proposes a new differential evolution (DE) algorithm for unconstrained continuous optimisation problems, termed JADE, that uses a small or 'micro' () population. The main contribution of the proposed DE is a new mutation operator, 'current-by-rand-to-pbest.' With a population size less than 10, JADE is able to solve some classical multimodal benchmark problems of 30 and 100 dimensions as reliably as some state-of-the-art DE algorithms using conventionally sized populations. The algorithm also compares favourably to other small population DE variants and classical DE.
引用
收藏
页码:4111 / 4120
页数:10
相关论文
共 50 条
  • [31] Multi-Population Inflationary Differential Evolution Algorithm with Adaptive Local Restart
    Di Carlo, Marilena
    Vasile, Massimiliano
    Minisci, Edmondo
    2015 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2015, : 632 - 639
  • [32] Population Based Optimization via Differential Evolution and Adaptive Fractional Gradient Descent
    Liu, Zijian
    Luo, Chunbo
    Ren, Peng
    Wang, Tingwei
    Min, Geyong
    FILOMAT, 2020, 34 (15) : 5173 - 5185
  • [33] Dual-Population Adaptive Differential Evolution Algorithm L-NTADE
    Stanovov, Vladimir
    Akhmedova, Shakhnaz
    Semenkin, Eugene
    MATHEMATICS, 2022, 10 (24)
  • [34] On Modification of Population-Based Approach Used in Adaptive Differential Evolution Algorithm
    Bujok, Petr
    ACTA POLYTECHNICA HUNGARICA, 2017, 14 (05) : 163 - 180
  • [35] Differential Evolution with Population and Strategy Parameter Adaptation
    Gonuguntla, V.
    Mallipeddi, R.
    Veluvolu, Kalyana C.
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
  • [36] Population reduction with individual similarity for differential evolution
    Li, Yuzhen
    Wang, Shihao
    Yang, Bo
    Chen, Hu
    Wu, Zhiqiang
    Yang, Hongyu
    ARTIFICIAL INTELLIGENCE REVIEW, 2023, 56 (05) : 3887 - 3949
  • [37] Small-World Hidden in Differential Evolution
    Skanderova, Lenka
    Fabian, Tomas
    Zelinka, Ivan
    2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2016, : 3354 - 3361
  • [38] An Adaptive Differential Evolution Algorithm
    Noman, Nasimul
    Bollegala, Danushka
    Iba, Hitoshi
    2011 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2011, : 2229 - 2236
  • [39] Adaptive Differential Evolution Based on Successful Experience Information
    Cheng, Lianzheng
    Wang, Yun
    Wang, Chao
    Mohamed, Ali Wagdy
    Xiao, Tiaojie
    IEEE ACCESS, 2020, 8 : 164611 - 164636
  • [40] Adaptive differential evolution with directional strategy and cloud model
    Gou, Jin
    Guo, Wang-Ping
    Hou, Feng
    Wang, Cheng
    Cai, Yi-Qiao
    APPLIED INTELLIGENCE, 2015, 42 (02) : 369 - 388