A Review of Population Initialization Techniques for Evolutionary Algorithms

被引:0
|
作者
Kazimipour, Borhan [1 ]
Li, Xiaodong [1 ]
Qin, A. K. [1 ,2 ]
机构
[1] RMIT Univ, Sch Comp Sci & Informat Technol, Melbourne, Vic 3000, Australia
[2] Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China
关键词
LOW-DISCREPANCY SEQUENCES; RANDOM NUMBER GENERATORS; GENETIC ALGORITHM; PERFORMANCE; OPPOSITION; STRATEGIES;
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
Although various population initialization techniques have been employed in evolutionary algorithms (EAs), there lacks a comprehensive survey on this research topic. To fill this gap and attract more attentions from EA researchers to this crucial yet less explored area, we conduct a systematic review of the existing population initialization techniques. Specifically, we categorize initialization techniques from three exclusive perspectives, i. e., randomness, compositionality and generality. Characteristics of the techniques belonging to each category are carefully analysed to further lead to several sub-categories. We also discuss several open issues related to this research topic, which demands further in-depth investigations.
引用
收藏
页码:2585 / 2592
页数:8
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