作者: Kalyanmoy Deb
DOI: 10.1007/BF02823145
关键词: Multi-objective optimization 、 Mathematical optimization 、 Engineering optimization 、 Metaheuristic 、 Multi-swarm optimization 、 Derivative-free optimization 、 Meta-optimization 、 Probabilistic-based design optimization 、 Computer science 、 Continuous optimization
摘要: Genetic algorithms (GAs) are search and optimization tools, which work differently compared to classical methods. Because of their broad applicability, ease use, global perspective, GAs have been increasingly applied various problems in the recent past. In this paper, a brief description simple GA is presented. Thereafter, handle constrained described. population approach, they also extended solve other efficiently, including multimodal, multiobjective scheduling problems, as well fuzzy-GA neuro-GA implementations. The purpose paper familiarize readers concept scope application.