Paper Info
Title
A Parallel Adaptive PSO Algorithm with Non-iterative Electrostatic Repulsion and Social Dynamic Neighborhood.
Abstract
This paper presents a variation on the DEPSO-2S algorithm, called Parallel Adaptive PSO (PA2PSO). The goals of the PA2PSO algorithm are to find the value closest the global minimum of the function evaluated improving the location as well as the interaction of the particles by means of two important characteristics: non-iterative electrostatic repulsion and social dynamic neighborhood, and to reduce the response time with a parallel implementation. The PA2PSO achieves in most cases positive results in solving benchmark test functions (unimodal and multimodal functions) compared with nine outstanding PSO algorithms.
Year
DOI
Venue
2016
10.1007/978-3-319-53480_056
INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA 2016)
Keywords
Field
DocType
Bio-inspired algorithms,Metaheuristics,Particle swarm optimization
Electrostatics,Particle swarm optimization,Mathematical optimization,Computer science,Response time,Artificial intelligence,Social dynamics,Machine learning,Metaheuristic
Conference
Volume
ISSN
Citations 
557
2194-5357
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Daniel Soto100.34
Wilson Soto201.69