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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| Format: | Thesis |
| Language: | en |
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2010
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| Online Access: | http://eprints.usm.my/41659/1/MOHAMMED_AZMI_AL-BETAR_HJ.pdf http://eprints.usm.my/41659/ |
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| _version_ | 1834502366271897600 |
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| author | Al-Betar, Mohammed Azmi |
| author_facet | Al-Betar, Mohammed Azmi |
| author_sort | Al-Betar, Mohammed Azmi |
| building | Hamzah Sendut Library |
| collection | Institutional Repository |
| content_provider | Universiti Sains Malaysia |
| content_source | USM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| 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 |
| id | my.usm.eprints.41659 |
| institution | Universiti Sains Malaysia |
| language | en |
| publishDate | 2010 |
| record_format | eprints |
| spelling | my.usm.eprints.41659 http://eprints.usm.my/41659/ Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling 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 NonPeerReviewed application/pdf en http://eprints.usm.my/41659/1/MOHAMMED_AZMI_AL-BETAR_HJ.pdf Al-Betar, Mohammed Azmi (2010) Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling. PhD thesis, Universiti Sains Malaysia. |
| spellingShingle | QA1 Mathematics (General) Al-Betar, Mohammed Azmi Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling |
| title | 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_short | 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 |
| topic | QA1 Mathematics (General) |
| url | http://eprints.usm.my/41659/1/MOHAMMED_AZMI_AL-BETAR_HJ.pdf http://eprints.usm.my/41659/ |
| url_provider | http://eprints.usm.my/ |