Fuzzy multiple heuristic orderings for course timetabling
In this paper, we address the issue of ordering events by simultaneously con- sidering three separate heuristics using fuzzy methods. Combinations of the fol- lowing three heuristic orderings are em- ployed: largest degree, saturation degree and largest enrollment. The fuzzy weight of an event is us...
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| Format: | Conference or Workshop Item |
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2005
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| _version_ | 1796855908907614208 |
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| author | Asmuni, H. |
| author_facet | Asmuni, H. |
| author_sort | Asmuni, H. |
| collection | ePrints |
| description | In this paper, we address the issue of ordering events by simultaneously con- sidering three separate heuristics using fuzzy methods. Combinations of the fol- lowing three heuristic orderings are em- ployed: largest degree, saturation degree and largest enrollment. The fuzzy weight of an event is used to represent how difficult it is to schedule. The decreasingly ordered events are sequentially chosen to be assigned to the last slot with least penalty cost value while the feasibility of the timetable is maintained throughout the process. Unscheduling and reschedul- ing events is performed until all events are scheduled. The proposed algorithm has been tested on 11 benchmark data sets of course timetabling problems and the re- sults show that this approach can produce good quality solutions with low require- ments for rescheduling. Moreover, there is signi?cant potential to extend the ap- proach further by including a larger range of criteria. |
| first_indexed | 2024-03-05T18:35:34Z |
| format | Conference or Workshop Item |
| id | utm.eprints-21848 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T18:35:34Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | utm.eprints-218482017-10-08T04:00:54Z http://eprints.utm.my/21848/ Fuzzy multiple heuristic orderings for course timetabling Asmuni, H. QA75 Electronic computers. Computer science In this paper, we address the issue of ordering events by simultaneously con- sidering three separate heuristics using fuzzy methods. Combinations of the fol- lowing three heuristic orderings are em- ployed: largest degree, saturation degree and largest enrollment. The fuzzy weight of an event is used to represent how difficult it is to schedule. The decreasingly ordered events are sequentially chosen to be assigned to the last slot with least penalty cost value while the feasibility of the timetable is maintained throughout the process. Unscheduling and reschedul- ing events is performed until all events are scheduled. The proposed algorithm has been tested on 11 benchmark data sets of course timetabling problems and the re- sults show that this approach can produce good quality solutions with low require- ments for rescheduling. Moreover, there is signi?cant potential to extend the ap- proach further by including a larger range of criteria. 2005 Conference or Workshop Item PeerReviewed Asmuni, H. (2005) Fuzzy multiple heuristic orderings for course timetabling. In: th United Kingdom Workshop on Computational Intelligence (UKCI05), 2005, London, UK. |
| spellingShingle | QA75 Electronic computers. Computer science Asmuni, H. Fuzzy multiple heuristic orderings for course timetabling |
| title | Fuzzy multiple heuristic orderings for course timetabling |
| title_full | Fuzzy multiple heuristic orderings for course timetabling |
| title_fullStr | Fuzzy multiple heuristic orderings for course timetabling |
| title_full_unstemmed | Fuzzy multiple heuristic orderings for course timetabling |
| title_short | Fuzzy multiple heuristic orderings for course timetabling |
| title_sort | fuzzy multiple heuristic orderings for course timetabling |
| topic | QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT asmunih fuzzymultipleheuristicorderingsforcoursetimetabling |