An adaptive artificial bee colony and late-acceptance hill-climbing algorithm for examination timetabling

Author:

Alzaqebah M.,Abdullah S.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Management Science and Operations Research,General Engineering,Software

Reference45 articles.

1. Abdullah, S., & Burke, E. K. (2006). A multi-start large neighbourhood search approach with local search methods for examination timetabling. In D. Long, S. F. Smith, D. Borrajo, & L. McCluskey (Eds.), International Conference on Automated Planning and Scheduling (ICAPS 2006), Cumbria, UK, 6–10 June (pp. 334–337).

2. Abdullah, S., Burke, E. K., & McCollum, B. (2007a). Using a randomised iterative improvement algorithm with composite neighbourhood structures for university course timetabling. In Metaheuristics: Progress in Complex Systems Optimization (Operations Research/Computer Science Interfaces Series) (Chap. 8, pp. 153–169). New York: Springer.

3. Abdullah, S., Ahmadi, S., Burke, E. K., & Dror, M. (2007b). Investigating Ahuja-Orlin’s large neighbourhood search approach for examination timetabling. OR Spectrum, 29(2), 351–372.

4. Abdullah, S., Turabieh, H., & McCollum, B. (2009). A hybridization of electromagnetic like mechanism and great deluge for examination timetabling problems. In HM2009: 6th International Workshop on Hybrid Metaheuristics, Udine (pp. 60–72).

5. Alzaqebah, M., & Abdullah, S. (2011a). Comparison of the selection strategy in the artificial bee colony algorithm for examination timetabling problems. International Journal of Soft Computing and Engineering, 1(5), 158–163.

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