Transformation of the university timetabling problem space through data pre-processing (granulation)

Timetabling is an important challenge faced by many organizations, especially organizations which require allocation of resources to a specific time and location. Due to the wide spread applications of scheduling, research in the area is also scattered and usually problem specific. Hence we are focusing our attention on educational institutions, however even within the scope of educational institutions the scheduling problem can still have several facets, these includes class scheduling, facilities scheduling, timetable scheduling, exam scheduling and many more. We have selected the area of exam scheduling as the main interest of this research work. In many educational institutions timetable is carried out manually and in most cases it is a trial and error approach. In some institutions the process of timetable generations relies heavily on the experience of the person in charge to be created making the task highly dependent on a person. Timetabling or scheduling has become a major problem in many organizations or institutions. Without automatic scheduling, great effort and ample time will be needed to prepare and optimize these schedules. For example in higher learning institutions, to satisfy multiple constraints examination and class scheduling such as eliminating clashes, and minimizing occurrence of two exams in a row are still a problem. However with intelligent systems, process automation can be carried out to produce feasible timetable with less resources and time. Timetabling or scheduling research do not only concentrates on generating feasible timetable but the efficiency of the solution generated is also sought after. Over the years attempts have been made to develop computer software to handle these activities. These research efforts evaluated various approaches, created new methods, produce promising findings and results. However, due to the inherent complexity of the problem, there is still a room for improvement of the current state of the art.

Publications

• S. Rahim, A. Bargiela, R. Qu, Domain transformation approach to deterministic optimization of examination timetables, Artificial Intelligence Research, 2(1):122-138, January 2013, doi: 10.5430/air.v2n1p122
• Rahim Siti Khatijah, Bargiela Andrzej, Granular Modelling of exam to slot allocation, Proc. 23rd European Conference on Modelling and Simulation, ECMS 2009, Madrid, Spain, pp.861-866, June 2009, PDF
• Rahim, S., Bargiela, A., Qu, R., Deterministic Optimisation of Examination Timetables, 25th European Conference on Operational Research, EURO 2012, Session TC-14, p.220-221, Vilnius, Latvia, July 2012

References

• Bargiela, A., Pedrycz, W., Granular computing: an introduction, Springer, 2003
• Pedrycz, W., Bargiela, A., Granular clustering: a granular signature of data, IEEE Trans. on Systems Man and Cybernetics, SMC-B, 32, 2, April 2002, 212-224, (doi: 10.1109/3477.990878 )
• Bargiela, A., Pedrycz, W., Toward a theory of Granular Computing for human-centred information processing, IEEE Trans. on Fuzzy Systems, vol. 16, 2, 2008, 320-330. (doi: 10.1109/TFUZZ.2007.905912)
• Bargiela, A., Pedrycz, W., The roots of granular computing, Proceedings of 2006 IEEE International Conference on Granular Computing, 806-809
• Bargiela, A., Pedrycz, W., Recursive information granulation: Aggregation and interpretation issues, IEEE Trans. on Systems Man and Cybernetics SMC-B, 33, 1, 17, 2003, 96-112. (10.1109/TSMCB.2003.808190)
• Bargiela, A., Pedrycz, W., Granular mappings, IEEE Transactions on Systems Man and Cybernetics SMC-A, vol. 35, 2, March 2005, 288-301 (doi: 10.1109/TSMCA.2005.843381)
• Bargiela, A., Pedrycz, W., A model of granular data: a design problem with the Tchebyschev FCM, Soft Computing, 9, 3, March 2005, 155-163 (doi: 10.1007/s00500-003-0339-2)
• Abdul Rahman, S, Bargiela, A., Burke, E.K., McCollum, B., Construction of Examination Timetables Based on Ordering Heuristics, Proc. 24th Int. Symposium on Computer and Information Sciences (ISCIS 2009), 727-732, Sept. 2009 (doi: 10.1109/ISCIS.2009.5291905)
• Abdul-Rahman, S., Burke E.K., Bargiela A., McCollum B., Ozcan E., A Constructive approach to examination timetabling based on adaptive decomposition and ordering, Annals of Operation Research, 2011, (doi: 10.1007/s10479-011-0999-8)
• Abdul Rahman, S, Burke, E.K., Bargiela, A., McCollum, B., A Construction Approach for Examinations Timetabling based on Adaptive Decomposition and Ordering, Practice and Theory of Automated Timetabling (PATAT 2010), Aug. 2010

To download a PDF file of the poster please click on the image