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Analysis of Population Diversity of Dynamic Probabilistic Particle Swarm Optimization Algorithms
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-03
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
In evolutionary algorithm, population diversity is an important factor for solving performance.
In this paper, combined with some population diversity analysis methods in other evolutionary algorithms, three indicators are introduced to be measures of population diversity in PSO algorithms, which are standard deviation of population fitness values, population entropy, and Manhattan norm of standard deviation in population positions.
The three measures are used to analyze the population diversity in a relatively new PSO variant—Dynamic Probabilistic Particle Swarm Optimization (DPPSO).
The results show that the three measure methods can fully reflect the evolution of population diversity in DPPSO algorithms from different angles, and we also discuss the impact of population diversity on the DPPSO variants.
The relevant conclusions of the population diversity on DPPSO can be used to analyze, design, and improve the DPPSO algorithms, thus improving optimization performance, which could also be beneficial to understand the working mechanism of DPPSO theoretically.
American Psychological Association (APA)
Ni, Qingjian& Deng, Jianming. 2014. Analysis of Population Diversity of Dynamic Probabilistic Particle Swarm Optimization Algorithms. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-496758
Modern Language Association (MLA)
Ni, Qingjian& Deng, Jianming. Analysis of Population Diversity of Dynamic Probabilistic Particle Swarm Optimization Algorithms. Mathematical Problems in Engineering No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-496758
American Medical Association (AMA)
Ni, Qingjian& Deng, Jianming. Analysis of Population Diversity of Dynamic Probabilistic Particle Swarm Optimization Algorithms. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-496758
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-496758