Bats echolocation-inspired algorithms for global optimisation problems

Swarm intelligence algorithms, are among popular metaheuristic methods, developed and inspired by the collective behaviour of swarms that have attracted significant attention of researchers. The works related to swarm intelligence algorithms include the development of the algorithm itself, its modif...

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Main Author:	Nafrizuan, Mat Yahya
Format:	Thesis
Language:	English
Published:	2016
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/18518/1/Bats%20echolocation-inspired%20algorithms%20for%20global%20optimisation%20problems..pdf
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id	my-ump-ir.18518
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spelling	my-ump-ir.185182023-05-08T02:36:32Z Bats echolocation-inspired algorithms for global optimisation problems 2016-02 Nafrizuan, Mat Yahya QA76 Computer software Swarm intelligence algorithms, are among popular metaheuristic methods, developed and inspired by the collective behaviour of swarms that have attracted significant attention of researchers. The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. This thesis presents works on swarm intelligence algorithms that are inspired by real echolocation of a colony of bats and its performance evaluation to solve optimisation problems. The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. An adaptive bats sonar algorithm is proposed for solving single objective optimisation problems. A modified adaptive bats sonar algorithm is then proposed for solving constrained optimisation problems. Furthermore, a dual-particle swarm optimisation-modified adaptive bats sonar algorithm is proposed for solving multi objective optimisation problems. The algorithm is a hybrid algorithm that operates using dual level search strategy that takes merits of a particle swarm optimisation algorithm and a modified adaptive bats sonar algorithm. The superior performances of the developed bats echolocation-inspired algorithms are verified through rigorous tests with optimisation benchmark test functions and problems. Further, the performances of the developed algorithms are assessed in solving selected practical problems in business, mechanical/manufacturing engineering and electrical engineering fields. The results validate the better performance of the developed algorithms in single objective optimisation, constrained optimisation and multi objective optimisation problems of various fields. 2016-02 Thesis http://umpir.ump.edu.my/id/eprint/18518/ http://umpir.ump.edu.my/id/eprint/18518/1/Bats%20echolocation-inspired%20algorithms%20for%20global%20optimisation%20problems..pdf pdf en public phd doctoral The University of Sheffield Automatic Control & Systems Engineering
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
collection	UMPSA Institutional Repository
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Nafrizuan, Mat Yahya Bats echolocation-inspired algorithms for global optimisation problems
description	Swarm intelligence algorithms, are among popular metaheuristic methods, developed and inspired by the collective behaviour of swarms that have attracted significant attention of researchers. The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. This thesis presents works on swarm intelligence algorithms that are inspired by real echolocation of a colony of bats and its performance evaluation to solve optimisation problems. The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. An adaptive bats sonar algorithm is proposed for solving single objective optimisation problems. A modified adaptive bats sonar algorithm is then proposed for solving constrained optimisation problems. Furthermore, a dual-particle swarm optimisation-modified adaptive bats sonar algorithm is proposed for solving multi objective optimisation problems. The algorithm is a hybrid algorithm that operates using dual level search strategy that takes merits of a particle swarm optimisation algorithm and a modified adaptive bats sonar algorithm. The superior performances of the developed bats echolocation-inspired algorithms are verified through rigorous tests with optimisation benchmark test functions and problems. Further, the performances of the developed algorithms are assessed in solving selected practical problems in business, mechanical/manufacturing engineering and electrical engineering fields. The results validate the better performance of the developed algorithms in single objective optimisation, constrained optimisation and multi objective optimisation problems of various fields.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Nafrizuan, Mat Yahya
author_facet	Nafrizuan, Mat Yahya
author_sort	Nafrizuan, Mat Yahya
title	Bats echolocation-inspired algorithms for global optimisation problems
title_short	Bats echolocation-inspired algorithms for global optimisation problems
title_full	Bats echolocation-inspired algorithms for global optimisation problems
title_fullStr	Bats echolocation-inspired algorithms for global optimisation problems
title_full_unstemmed	Bats echolocation-inspired algorithms for global optimisation problems
title_sort	bats echolocation-inspired algorithms for global optimisation problems
granting_institution	The University of Sheffield
granting_department	Automatic Control & Systems Engineering
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/18518/1/Bats%20echolocation-inspired%20algorithms%20for%20global%20optimisation%20problems..pdf
_version_	1783732035325526016

Bats echolocation-inspired algorithms for global optimisation problems

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