![](/images/graphics-bg.png)
Artificial Bee Colony Algorithm Based on K-Means Clustering for Multiobjective Optimal Power Flow Problem
Joint Authors
Chen, Hanning
Sun, Liling
Hu, Jing-tao
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-03
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
An improved multiobjective ABC algorithm based on K-means clustering, called CMOABC, is proposed.
To fasten the convergence rate of the canonical MOABC, the way of information communication in the employed bees’ phase is modified.
For keeping the population diversity, the multiswarm technology based on K-means clustering is employed to decompose the population into many clusters.
Due to each subcomponent evolving separately, after every specific iteration, the population will be reclustered to facilitate information exchange among different clusters.
Application of the new CMOABC on several multiobjective benchmark functions shows a marked improvement in performance over the fast nondominated sorting genetic algorithm (NSGA-II), the multiobjective particle swarm optimizer (MOPSO), and the multiobjective ABC (MOABC).
Finally, the CMOABC is applied to solve the real-world optimal power flow (OPF) problem that considers the cost, loss, and emission impacts as the objective functions.
The 30-bus IEEE test system is presented to illustrate the application of the proposed algorithm.
The simulation results demonstrate that, compared to NSGA-II, MOPSO, and MOABC, the proposed CMOABC is superior for solving OPF problem, in terms of optimization accuracy.
American Psychological Association (APA)
Sun, Liling& Hu, Jing-tao& Chen, Hanning. 2015. Artificial Bee Colony Algorithm Based on K-Means Clustering for Multiobjective Optimal Power Flow Problem. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-18.
https://search.emarefa.net/detail/BIM-1074668
Modern Language Association (MLA)
Sun, Liling…[et al.]. Artificial Bee Colony Algorithm Based on K-Means Clustering for Multiobjective Optimal Power Flow Problem. Mathematical Problems in Engineering No. 2015 (2015), pp.1-18.
https://search.emarefa.net/detail/BIM-1074668
American Medical Association (AMA)
Sun, Liling& Hu, Jing-tao& Chen, Hanning. Artificial Bee Colony Algorithm Based on K-Means Clustering for Multiobjective Optimal Power Flow Problem. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-18.
https://search.emarefa.net/detail/BIM-1074668
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074668