Article

Bacterial Foraging Algorithm with Varying Population for Optimal Power Flow

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J. R. SaundersAuthors Info & Claims

Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing

Pages 32 - 41

https://doi.org/10.1007/978-3-540-71805-5_4

Published: 22 June 2009 Publication History

Abstract

This paper proposes a novel optimization algorithm, Bacterial Foraging Algorithm with Varying Population (BFAVP), to solve Optimal Power Flow (OPF) problems. Most of the conventional Evolutionary Algorithms (EAs) are based on fixed population evaluation, which does not achieve the full potential of effective search. In this paper, a varying population algorithm is developed from the study of bacterial foraging behavior. This algorithm, for the first time, explores the underlying mechanisms of bacterial chemotaxis, quorum sensing and proliferation, etc., which have been successfully merged into the varying-population frame. The BFAVP algorithm has been applied to the OPF problem and it has been evaluated by simulation studies, which were undertaken on an IEEE 30-bus test system, in comparison with a Particle Swarm Optimizer (PSO) [1].

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Cited By

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Chunsheng S(2018)Study on Optimization of Bacteria Foraging Optimization Algorithm combined with Roulette Wheel MethodProceedings of the 2nd International Conference on Business and Information Management10.1145/3278252.3278270(15-17)Online publication date: 20-Sep-2018
https://dl.acm.org/doi/10.1145/3278252.3278270
Mahmoodabadi MTaherkhorsandi MMaafi RCastillo-Villar K(2015)A novel multi-objective optimisation algorithmInternational Journal of Intelligent Engineering Informatics10.1504/IJIEI.2015.0730883:4(369-386)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1504/IJIEI.2015.073088
Minhas FArif M(2011)MOXApplied Soft Computing10.1016/j.asoc.2011.07.02011:8(4614-4625)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1016/j.asoc.2011.07.020
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Published In

Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing

June 2009

751 pages

ISBN:9783540718048

Editor:
Mario Giacobini
Department of Animal Production, Epidemiology and Ecology, University of Torino, Italy

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 22 June 2009

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Chunsheng S(2018)Study on Optimization of Bacteria Foraging Optimization Algorithm combined with Roulette Wheel MethodProceedings of the 2nd International Conference on Business and Information Management10.1145/3278252.3278270(15-17)Online publication date: 20-Sep-2018
https://dl.acm.org/doi/10.1145/3278252.3278270
Mahmoodabadi MTaherkhorsandi MMaafi RCastillo-Villar K(2015)A novel multi-objective optimisation algorithmInternational Journal of Intelligent Engineering Informatics10.1504/IJIEI.2015.0730883:4(369-386)Online publication date: 1-Nov-2015
https://dl.acm.org/doi/10.1504/IJIEI.2015.073088
Minhas FArif M(2011)MOXApplied Soft Computing10.1016/j.asoc.2011.07.02011:8(4614-4625)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1016/j.asoc.2011.07.020
Biswas ADas SAbraham ADasgupta S(2010)Stability analysis of the reproduction operator in bacterial foraging optimizationTheoretical Computer Science10.1016/j.tcs.2010.03.005411:21(2127-2139)Online publication date: 1-May-2010
https://dl.acm.org/doi/10.1016/j.tcs.2010.03.005
Dang JBrabazon AO'Neill MEdelman D(2008)Option model calibration using a bacterial foraging optimization algorithmProceedings of the 2008 conference on Applications of evolutionary computing10.5555/1787943.1787957(113-122)Online publication date: 26-Mar-2008
https://dl.acm.org/doi/10.5555/1787943.1787957
Das SDasgupta SBiswas AAbraham AKonar AZadeh LBadr YAbraham AOhsawa YChbeir RFerri FKoeppen MLaurent D(2008)Stability of the chemotactic dynamics in bacterial foraging optimization algorithmProceedings of the 5th international conference on Soft computing as transdisciplinary science and technology10.1145/1456223.1456276(245-251)Online publication date: 28-Oct-2008
https://dl.acm.org/doi/10.1145/1456223.1456276

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An effective bacterial foraging optimizer for global optimization

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