A review of optimization swarm intelligence-inspired algorithms with type-2 fuzzy logic parameter adaptation

被引：0
作者：
Fevrier Valdez
机构：
[1] Tijuana Institute of Technology/Tecnológico Nacional de México,
来源：
Soft Computing | 2020年 / 24卷
关键词：
Optimization methods; Collective intelligence; Swarm algorithms; Parameter adaptation; Type-2 fuzzy logic;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, a survey about the algorithms based on swarm intelligence with parameter adaptation using some techniques to achieve the best results is presented. In this case, we analyzed the most popular algorithms such as ant colony optimization, particle swarm optimization, bee colony optimization, bat algorithm, firefly algorithm and cuckoo search. These algorithms are referenced in the paper because they have demonstrated to be superior with respect to the other optimization methods based on swarms with parameter adaptation using type-2 fuzzy logic in some applications, and also the algorithms are inspired on swarm intelligence.
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页码：215 / 226
页数：11
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