Paper Info
Title
An Alternative Approach For Particle Swarm Optimisation Using Serendipity
Abstract
In the study of metaheuristic techniques, it is very common to deal with a problem known as premature convergence. This problem is widely studied in swarm intelligence algorithms such as particle swarm optimisation (PSO). Most approaches to the problem consider the generation and/or positioning of individuals in the search space randomly. This paper approaches the issue using the concept of serendipity and its adaptation in this new context. Several strategies that implement serendipity were evaluated in order to develop a PSO variant based on this concept. The results were compared with the traditional PSO considering the quality of the solutions and the ability to find global optimum. The new algorithm was also compared with a PSO variant of the literature. The experiments showed promising results related to the criteria mentioned above, but there is the need for additional adjustments to decrease the runtime.
Year
DOI
Venue
2018
10.1504/IJBIC.2017.10004328
INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION
Keywords
Field
DocType
particle swarm optimisation, PSO, SBPSO, serendipity, swarm intelligence, global optimisation, bio-inspired computation, metaheuristic
Particle swarm optimization,Mathematical optimization,Premature convergence,Swarm intelligence,Global optimum,Multi-swarm optimization,Mathematics,Serendipity,Metaheuristic
Journal
Volume
Issue
ISSN
11
2
1758-0366
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Fábio A. Procópio de Paiva122.06
José Alfredo F. Costa25210.11
msc claudio r m silva322.40