A Crossover Bacterial Foraging Optimization Algorithm

This paper presents a modified bacterial foraging optimization algorithm called crossover bacterial foraging optimization algorithm, which inherits the crossover technique of genetic algorithm. This can be used for improvising the evaluation of optimal objective function values. The idea of using cr...

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Main Authors: Rutuparna Panda, Manoj Kumar Naik
Format: Article
Language:English
Published: Wiley 2012-01-01
Series:Applied Computational Intelligence and Soft Computing
Online Access:http://dx.doi.org/10.1155/2012/907853
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author Rutuparna Panda
Manoj Kumar Naik
author_facet Rutuparna Panda
Manoj Kumar Naik
author_sort Rutuparna Panda
collection DOAJ
description This paper presents a modified bacterial foraging optimization algorithm called crossover bacterial foraging optimization algorithm, which inherits the crossover technique of genetic algorithm. This can be used for improvising the evaluation of optimal objective function values. The idea of using crossover mechanism is to search nearby locations by offspring (50 percent of bacteria), because they are randomly produced at different locations. In the traditional bacterial foraging optimization algorithm, search starts from the same locations (50 percent of bacteria are replicated) which is not desirable. Seven different benchmark functions are considered for performance evaluation. Also, comparison with the results of previous methods is presented to reveal the effectiveness of the proposed algorithm.
format Article
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institution Kabale University
issn 1687-9724
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language English
publishDate 2012-01-01
publisher Wiley
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series Applied Computational Intelligence and Soft Computing
spelling doaj-art-a1e46ffd5af24f7f8f72a9ed9d23224e2025-08-20T03:38:38ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322012-01-01201210.1155/2012/907853907853A Crossover Bacterial Foraging Optimization AlgorithmRutuparna Panda0Manoj Kumar Naik1Department of Electronics and Telecommunication Engineering, VSS University of Technology, Burla 768018, IndiaDepartment of Electronics and Telecommunication Engineering, VSS University of Technology, Burla 768018, IndiaThis paper presents a modified bacterial foraging optimization algorithm called crossover bacterial foraging optimization algorithm, which inherits the crossover technique of genetic algorithm. This can be used for improvising the evaluation of optimal objective function values. The idea of using crossover mechanism is to search nearby locations by offspring (50 percent of bacteria), because they are randomly produced at different locations. In the traditional bacterial foraging optimization algorithm, search starts from the same locations (50 percent of bacteria are replicated) which is not desirable. Seven different benchmark functions are considered for performance evaluation. Also, comparison with the results of previous methods is presented to reveal the effectiveness of the proposed algorithm.http://dx.doi.org/10.1155/2012/907853
spellingShingle Rutuparna Panda
Manoj Kumar Naik
A Crossover Bacterial Foraging Optimization Algorithm
Applied Computational Intelligence and Soft Computing
title A Crossover Bacterial Foraging Optimization Algorithm
title_full A Crossover Bacterial Foraging Optimization Algorithm
title_fullStr A Crossover Bacterial Foraging Optimization Algorithm
title_full_unstemmed A Crossover Bacterial Foraging Optimization Algorithm
title_short A Crossover Bacterial Foraging Optimization Algorithm
title_sort crossover bacterial foraging optimization algorithm
url http://dx.doi.org/10.1155/2012/907853
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AT manojkumarnaik acrossoverbacterialforagingoptimizationalgorithm
AT rutuparnapanda crossoverbacterialforagingoptimizationalgorithm
AT manojkumarnaik crossoverbacterialforagingoptimizationalgorithm