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Novel Adaptive Bacteria Foraging Algorithms for Global Optimization
Joint Authors
Ghani, N. Maniha Abd.
Nasir, Ahmad N. K.
Tokhi, M. O.
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-25
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper presents improved versions of bacterial foraging algorithm (BFA).
The chemotaxis feature of bacteria through random motion is an effective strategy for exploring the optimum point in a search area.
The selection of small step size value in the bacteria motion leads to high accuracy in the solution but it offers slow convergence.
On the contrary, defining a large step size in the motion provides faster convergence but the bacteria will be unable to locate the optimum point hence reducing the fitness accuracy.
In order to overcome such problems, novel linear and nonlinear mathematical relationships based on the index of iteration, index of bacteria, and fitness cost are adopted which can dynamically vary the step size of bacteria movement.
The proposed algorithms are tested with several unimodal and multimodal benchmark functions in comparison with the original BFA.
Moreover, the application of the proposed algorithms in modelling of a twin rotor system is presented.
The results show that the proposed algorithms outperform the predecessor algorithm in all test functions and acquire better model for the twin rotor system.
American Psychological Association (APA)
Nasir, Ahmad N. K.& Tokhi, M. O.& Ghani, N. Maniha Abd.. 2014. Novel Adaptive Bacteria Foraging Algorithms for Global Optimization. Applied Computational Intelligence and Soft Computing،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-476139
Modern Language Association (MLA)
Nasir, Ahmad N. K.…[et al.]. Novel Adaptive Bacteria Foraging Algorithms for Global Optimization. Applied Computational Intelligence and Soft Computing No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-476139
American Medical Association (AMA)
Nasir, Ahmad N. K.& Tokhi, M. O.& Ghani, N. Maniha Abd.. Novel Adaptive Bacteria Foraging Algorithms for Global Optimization. Applied Computational Intelligence and Soft Computing. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-476139
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-476139