Firefly Algorithm and Grey Wolf Optimizer for Constrained Real-Parameter Optimization

被引：1
|
作者：
Rodriguez, Luis [1 ]
Castillo, Oscar [1 ]
Garcia, Mario [1 ]
Soria, Jose [1 ]
机构：
[1] Tijuana Inst Technol, Tijuana, BC, Canada
来源：
FUZZY TECHNIQUES: THEORY AND APPLICATIONS | 2019年 / 1000卷
关键词：
Grey Wolf Optimizer; Firefly Algorithm; Constraints; Complex problems; Study; Optimization; EDGE-DETECTION METHOD; FUZZY; ADAPTATION; SYSTEMS; TYPE-1; CONTROLLERS;
D O I：
10.1007/978-3-030-21920-8_47
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The main goal of this paper is to present the performance of two popular algorithms, the first is the Firefly Algorithm (FA) and the second one is the Grey Wolf Optimizer (GWO) algorithm for complex problems. In this case the problems that we are presenting are of the CEC 2017 Competition on Constrained Real-Parameter Optimization in order to realize a brief analysis, study and comparison between the FA and GWO algorithms respectively.
引用
收藏
页码：531 / 541
页数：11
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