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
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