Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms

This paper presents three novel hybrid optimization algorithms based on bacterial foraging and spiral dynamics algorithms and their application to modelling of flexible maneuvering systems. Hybrid bacteria-chemotaxis spiral- dynamics algorithm is a combination of chemotaxis strategy in bacterial for...

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Main Authors:	Ahmad Nor Kasruddin, Nasir, Tokhi, M. O., Nor Maniha, Abd Ghani
Format:	Conference or Workshop Item
Language:	English
Published:	2013
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/4232/ http://umpir.ump.edu.my/id/eprint/4232/1/fkee-2013-kasruddin-novel_hybrid_bacterial_abs_only.pdf

id	ump-4232
recordtype	eprints
spelling	ump-42322018-03-19T05:57:48Z http://umpir.ump.edu.my/id/eprint/4232/ Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms Ahmad Nor Kasruddin, Nasir Tokhi, M. O. Nor Maniha, Abd Ghani TK Electrical engineering. Electronics Nuclear engineering This paper presents three novel hybrid optimization algorithms based on bacterial foraging and spiral dynamics algorithms and their application to modelling of flexible maneuvering systems. Hybrid bacteria-chemotaxis spiral- dynamics algorithm is a combination of chemotaxis strategy in bacterial foraging algorithm and linear adaptive spiral dynamics algorithm. Chemotactic behaviour of bacteria is a good strategy for fast exploration if large value of step size is defined in the motion. However, this results in oscillation in the search process and bacteria cannot reach optimum fitness accuracy in the final solution. On the contrary, spiral dynamics provides good exploitation strategy due to its dynamic step size. However, it suffers from getting trapped at local optima due to poor exploration in the diversification phase. Employing the chemotaxis and spiral dynamics strategies at the initial and final stages respectively will thus balance the exploration and exploitation. Hybrid spiral-bacterial foraging algorithm and hybrid chemotaxis-spiral algorithm, on the other hand are developed based on adaptation of spiral dynamics model into chemotaxis phase of bacterial foraging with the aim to guide bacteria movement globally. The proposed algorithms are used to optimize parameters of a linear parametric model of a flexible robot manipulator system. The performances of the proposed hybrid algorithms are presented in comparison to their predecessor algorithms in terms of fitness accuracy, time-domain and frequency-domain responses of the models. The results show that the proposed algorithms achieve better performance. 2013-09-09 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4232/1/fkee-2013-kasruddin-novel_hybrid_bacterial_abs_only.pdf Ahmad Nor Kasruddin, Nasir and Tokhi, M. O. and Nor Maniha, Abd Ghani (2013) Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms. In: Proceeding of The 13th Annual UK Workshop on Computational Intelligence UKCI 2013, September 9-11, 2013 , University of Surrey, Guildford, United Kingdom. pp. 199-205..
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Ahmad Nor Kasruddin, Nasir Tokhi, M. O. Nor Maniha, Abd Ghani Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms
description	This paper presents three novel hybrid optimization algorithms based on bacterial foraging and spiral dynamics algorithms and their application to modelling of flexible maneuvering systems. Hybrid bacteria-chemotaxis spiral- dynamics algorithm is a combination of chemotaxis strategy in bacterial foraging algorithm and linear adaptive spiral dynamics algorithm. Chemotactic behaviour of bacteria is a good strategy for fast exploration if large value of step size is defined in the motion. However, this results in oscillation in the search process and bacteria cannot reach optimum fitness accuracy in the final solution. On the contrary, spiral dynamics provides good exploitation strategy due to its dynamic step size. However, it suffers from getting trapped at local optima due to poor exploration in the diversification phase. Employing the chemotaxis and spiral dynamics strategies at the initial and final stages respectively will thus balance the exploration and exploitation. Hybrid spiral-bacterial foraging algorithm and hybrid chemotaxis-spiral algorithm, on the other hand are developed based on adaptation of spiral dynamics model into chemotaxis phase of bacterial foraging with the aim to guide bacteria movement globally. The proposed algorithms are used to optimize parameters of a linear parametric model of a flexible robot manipulator system. The performances of the proposed hybrid algorithms are presented in comparison to their predecessor algorithms in terms of fitness accuracy, time-domain and frequency-domain responses of the models. The results show that the proposed algorithms achieve better performance.
format	Conference or Workshop Item
author	Ahmad Nor Kasruddin, Nasir Tokhi, M. O. Nor Maniha, Abd Ghani
author_facet	Ahmad Nor Kasruddin, Nasir Tokhi, M. O. Nor Maniha, Abd Ghani
author_sort	Ahmad Nor Kasruddin, Nasir
title	Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms
title_short	Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms
title_full	Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms
title_fullStr	Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms
title_full_unstemmed	Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms
title_sort	novel hybrid bacterial foraging and spiral dynamics algorithms
publishDate	2013
url	http://umpir.ump.edu.my/id/eprint/4232/ http://umpir.ump.edu.my/id/eprint/4232/1/fkee-2013-kasruddin-novel_hybrid_bacterial_abs_only.pdf
first_indexed	2023-09-18T21:58:42Z
last_indexed	2023-09-18T21:58:42Z
_version_	1777414253082312704

Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms

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