Multi-swarm Optimization Algorithm Based on Firefly and Particle Swarm Optimization Techniques

被引：5
|
作者：
Kadavy, Tomas [1 ]
Pluhacek, Michal [1 ]
Viktorin, Adam [1 ]
Senkerik, Roman [1 ]
机构：
[1] Tomas Bata Univ Zlin, Fac Appl Informat, TG Masaryka 5555, Zlin 76001, Czech Republic
来源：
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2018, PT I | 2018年 / 10841卷
关键词：
Firefly Algorithm; Particle Swarm Optimization; Hybridization; Multi-swarm;
D O I：
10.1007/978-3-319-91253-0_38
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the two hybrid swarm-based metaheuristic algorithms are tested and compared. The first hybrid is already existing Firefly Particle Swarm Optimization (FFPSO), which is based, as the name suggests, on Firefly Algorithm (FA) and Particle Swarm Optimization (PSO). The secondly proposed hybrid is an algorithm using the multi-swarm method to merge FA and PSO. The performance of our developed algorithm is tested and compared with the FFPSO and canonical FA. Comparisons have been conducted on five selected benchmark functions, and the results have been evaluated for statistical significance using Friedman rank test.
引用
收藏
页码：405 / 416
页数：12
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