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| Content Provider | Springer Nature Link |
|---|---|
| Author | Abdul Rahman, Syariza Burke, Edmund K. Bargiela, Andrzej McCollum, Barry Özcan, Ender |
| Copyright Year | 2011 |
| Abstract | In this study, we investigate an adaptive decomposition and ordering strategy that automatically divides examinations into difficult and easy sets for constructing an examination timetable. The examinations in the difficult set are considered to be hard to place and hence are listed before the ones in the easy set in the construction process. Moreover, the examinations within each set are ordered using different strategies based on graph colouring heuristics. Initially, the examinations are placed into the easy set. During the construction process, examinations that cannot be scheduled are identified as the ones causing infeasibility and are moved forward in the difficult set to ensure earlier assignment in subsequent attempts. On the other hand, the examinations that can be scheduled remain in the easy set. Within the easy set, a new subset called the boundary set is introduced to accommodate shuffling strategies to change the given ordering of examinations. The proposed approach, which incorporates different ordering and shuffling strategies, is explored on the Carter benchmark problems. The empirical results show that the performance of our algorithm is broadly comparable to existing constructive approaches. |
| Starting Page | 3 |
| Ending Page | 21 |
| Page Count | 19 |
| File Format | |
| ISSN | 02545330 |
| Journal | Annals of Operations Research |
| Volume Number | 218 |
| Issue Number | 1 |
| e-ISSN | 15729338 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2011-10-13 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Timetabling Decomposition Graph colouring Heuristic Grouping Operations Research/Decision Theory Combinatorics Theory of Computation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Management Science and Operations Research |
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