Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling

University Course Timetabling Problem (UCTP) is a hard combinatorial scheduling problem. Harmony Search Algorithm (HSA) is a recent metaheuristic population-based method. The major thrust of this algorithm lies in its ability to integrate the key components of populationbased methods and local se...

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Main Author:	Al-Betar, Mohammed Azmi
Format:	Thesis
Language:	English
Published:	2010
Subjects:	QA1 Mathematics (General)
Online Access:	http://eprints.usm.my/41659/1/MOHAMMED_AZMI_AL-BETAR_HJ.pdf
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id	my-usm-ep.41659
record_format	uketd_dc
spelling	my-usm-ep.416592019-04-12T05:26:50Z Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling 2010-06 Al-Betar, Mohammed Azmi QA1 Mathematics (General) University Course Timetabling Problem (UCTP) is a hard combinatorial scheduling problem. Harmony Search Algorithm (HSA) is a recent metaheuristic population-based method. The major thrust of this algorithm lies in its ability to integrate the key components of populationbased methods and local search-based methods in the same optimisation model. This dissertation presents a HSA adapted for UCTP. The adaptation involved modifying the HSA operators. The results were within the range of state of the art. However, some shortcomings in the convergence rate and local exploitation were identified and addressed through hybridisation with known metaheuristic components. Three hybridized versions are proposed which are incremental improvements over the preceding version: (i) Modified Harmony Search Algorithm (MHSA); (ii) Harmony Search Algorithm with Multi-Pitch Adjusting Rate (HSA-MPAR), and (iii) Hybrid Harmony Search Algorithm (HHSA). The results were compared against 21 other methods using eleven de facto standard dataset of different sizes and complexity. The proposed hybridized versions achieved the optimal solution for the small datasets, with two best overall results for the medium datasets. Furthermore, in the large and most complex dataset the proposed hybrid methods achieved the best result. 2010-06 Thesis http://eprints.usm.my/41659/ http://eprints.usm.my/41659/1/MOHAMMED_AZMI_AL-BETAR_HJ.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA1 Mathematics (General)
spellingShingle	QA1 Mathematics (General) Al-Betar, Mohammed Azmi Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling
description	University Course Timetabling Problem (UCTP) is a hard combinatorial scheduling problem. Harmony Search Algorithm (HSA) is a recent metaheuristic population-based method. The major thrust of this algorithm lies in its ability to integrate the key components of populationbased methods and local search-based methods in the same optimisation model. This dissertation presents a HSA adapted for UCTP. The adaptation involved modifying the HSA operators. The results were within the range of state of the art. However, some shortcomings in the convergence rate and local exploitation were identified and addressed through hybridisation with known metaheuristic components. Three hybridized versions are proposed which are incremental improvements over the preceding version: (i) Modified Harmony Search Algorithm (MHSA); (ii) Harmony Search Algorithm with Multi-Pitch Adjusting Rate (HSA-MPAR), and (iii) Hybrid Harmony Search Algorithm (HHSA). The results were compared against 21 other methods using eleven de facto standard dataset of different sizes and complexity. The proposed hybridized versions achieved the optimal solution for the small datasets, with two best overall results for the medium datasets. Furthermore, in the large and most complex dataset the proposed hybrid methods achieved the best result.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Al-Betar, Mohammed Azmi
author_facet	Al-Betar, Mohammed Azmi
author_sort	Al-Betar, Mohammed Azmi
title	Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling
title_short	Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling
title_full	Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling
title_fullStr	Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling
title_full_unstemmed	Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling
title_sort	adapting and hybridising harmony search with metaheuristic components for university course timetabling
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Komputer
publishDate	2010
url	http://eprints.usm.my/41659/1/MOHAMMED_AZMI_AL-BETAR_HJ.pdf
_version_	1747820951449370624

Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling

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