Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables
This paper tackles university course timetabling problems (UCTP) to find a (near) optimal solution (timetable) while satisfying hard constraints (essential requirements) and minimizing as much as possible the violations of the soft constrains (desirable requirements). In this study, we apply three a...
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my.uniten.dspace-295942023-12-28T15:05:44Z Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables Abdullah S. Shaker K. Shaker H. 23395783300 35231134200 55990421500 Great deluge Hill climbing algorithm Round robin Simulated annealing University course timetabling problem This paper tackles university course timetabling problems (UCTP) to find a (near) optimal solution (timetable) while satisfying hard constraints (essential requirements) and minimizing as much as possible the violations of the soft constrains (desirable requirements). In this study, we apply three algorithms, that is, Great Deluge, Simulated Annealing and Hill Climbing where the Round Robin algorithm is used as control strategy in choosing the algorithm to be employed at the current stage. The performance of the approach is tested with over two sets of benchmark datasets, that is, enrolment-based course timetabling and curriculum-based course timetabling (UD1) in comparison with a set of state-of-the-art methods from the literature. The experimental results show that the proposed approach is able to produce competitive results for the test UCTPs. � 2011 Academic Journals. Final 2023-12-28T07:05:44Z 2023-12-28T07:05:44Z 2011 Article 2-s2.0-79957936133 https://www.scopus.com/inward/record.uri?eid=2-s2.0-79957936133&partnerID=40&md5=761b6422abca790ef38beffc44af1e0b https://irepository.uniten.edu.my/handle/123456789/29594 6 6 1452 1462 Scopus |
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Great deluge Hill climbing algorithm Round robin Simulated annealing University course timetabling problem |
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Great deluge Hill climbing algorithm Round robin Simulated annealing University course timetabling problem Abdullah S. Shaker K. Shaker H. Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables |
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This paper tackles university course timetabling problems (UCTP) to find a (near) optimal solution (timetable) while satisfying hard constraints (essential requirements) and minimizing as much as possible the violations of the soft constrains (desirable requirements). In this study, we apply three algorithms, that is, Great Deluge, Simulated Annealing and Hill Climbing where the Round Robin algorithm is used as control strategy in choosing the algorithm to be employed at the current stage. The performance of the approach is tested with over two sets of benchmark datasets, that is, enrolment-based course timetabling and curriculum-based course timetabling (UD1) in comparison with a set of state-of-the-art methods from the literature. The experimental results show that the proposed approach is able to produce competitive results for the test UCTPs. � 2011 Academic Journals. |
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23395783300 |
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23395783300 Abdullah S. Shaker K. Shaker H. |
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Abdullah S. Shaker K. Shaker H. |
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Abdullah S. |
title |
Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables |
title_short |
Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables |
title_full |
Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables |
title_fullStr |
Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables |
title_full_unstemmed |
Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables |
title_sort |
investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables |
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2023 |
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1806423359398871040 |
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13.211869 |