Genetic Algorithms: Brief review on Genetic Algorithms for Global Optimization Problems

被引：31

作者：

Anwaar, Aliza ^{[1
]}

Ashraf, Adnan ^{[2
]}

Bangyal, Waqas Haider Khan ^{[3
]}

Iqbal, Muddesar ^{[4
]}

机构：

[1] Univ Sialkot USKT, Dept Comp Sci, Sialkot, Pakistan

[2] Beijing Inst Technol, Sch Comp Sci, Beijing Lab Intelligent Informat Technol, Beijing 100081, Peoples R China

[3] Kohsar Univ, Dept Comp Sci, Murree, Pakistan

[4] London Southbank Univ, Div Comp Sci & Informaiton, Sch Engn, London, England

来源：

2022 HUMAN-CENTERED COGNITIVE SYSTEMS, HCCS | 2022年

关键词：

Genetic Algorithm; Taxonomy; GA; PARTICLE SWARM OPTIMIZATION; POPULATION-BASED ALGORITHMS; INITIALIZATION;

D O I：

10.1109/HCCS55241.2022.10090327

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An intelligent bionic algorithm with great global optimization potential, the genetic algorithm evolved in a manner analogous to the natural process of genetic evolution in living creatures. This paper first explains the foundation of genetic algorithms, which is based on Darwin's "survival of the fittest" principle, then outlining the algorithm's primary features and briefly discussing its drawbacks. The structural and thorough view of genetic algorithms is presented in this review work. Furthermore, taxonomy and the applications and application-specific genetic operators. This review paper's challenges and issues, as well as their answers, address every facet of GAs.

引用

页码：80 / 85

页数：6

共 44 条

[1] Fast robotic pencil drawing based on image evolution by means of genetic algorithm [J].