Statistical analysis of a multi-objective optimization algorithm based on a model of particles with vorticity behavior

被引：26
|
作者：
Meza, Joaquin [1 ]
Espitia, Helbert [1 ]
Montenegro, Carlos [1 ]
Gonzalez Crespo, Ruben [2 ]
机构：
[1] Univ Distrital Francisco Jose de Caldas, Carrera 8 40-62, Bogota, Colombia
[2] Univ Int La Rioja UNIR, Rectorado Via Rey Juan Carlos 1,41, Logrono, La Rioja, Spain
来源：
SOFT COMPUTING | 2016年 / 20卷 / 09期
关键词：
Multi-objective optimization; Particle swarm; Vorticity; EVOLUTIONARY ALGORITHM; PSO;
D O I：
10.1007/s00500-015-1972-2
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, a strategy for multi-objective optimization based upon the behavior of a particle swarm with rotational and linear motion is presented. The strategy for multi-objective optimization is based upon the emulation of the linear and circular movements of a swarm (flock). Thus emerges the physical basis for the cognitive model, which in conjunction with exploration-exploitation results in the proposal of a cognitive algorithm, which is tested through several multi-objective optimization functions. The algorithm proposed is compared with standard particle swarm optimization multi-objective via statistical analysis.
引用
收藏
页码：3521 / 3536
页数：16
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