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School Of Computer Science                                 

                                                       

     asap

             automated scheduling      

             optimisation & planning  


 

Kopivosian kuma  toinsanan

 


Joe Henry Obit
Automated Scheduling, optimisation

And Planning (ASAP)
School of Computer Science and IT
University of Nottingham
Jubilee Campus, Wollaton Road
Nottingham, NG8 1BB, UK

Tel: +44 115 846 6525
jzh@cs.nott.ac.uk

School Phone List

PhD Student

Educational Timetabling

Room

C87

Research Interests

Multi-Agent
Scheduling
Meta-heuristic

Hyper-heuristic

Heuristic
Combinatorial Optimisation

Links

Bookmarks

References

 

Supervisor

Dr. Dario Landa-Silva

Dr. Rong Qu

 


Research

Timetabling is a process of allocation, subject to constraints of given resources to objectives being placed in space time, in such a way as to satisfy as nearly as possible to set of desirable objectives.  The construction of a course timetable to ensure all activities are in place accordingly is a common problem for all institutions of higher learning.  Many factors contribute for this complexity such as, the requirements to satisfy the hard and soft constraints.

 

            The complexity of the timetabling has attracted the attention of the AI community to contribute their works in solving the problems. It has identified that the advanced algorithms such as evolutionary algorithm will not fully solved the complexity of the timetable problem especially when dealing with large instance.  As a result, few researchers have proposed the decomposition method to break the large instance into a small sub problem until the algorithms are able to handle and find the optimal solution. The process of decomposition method has been also studied, where the used of heuristic method to split large instance into small problem until each instance is small enough to be solved by the local search algorithms. Besides that the Distributed Multi-agent system is also has been used to solve the timetabling problems.

 


 

 

Publications:

 

Joe Henry Obit, Dario Landa-Silva, Marc Sevaux, Djamila Ouelhadj. Non-Linear Great Deluge with Reinforcement Learning for University Course Timetabling. Under review (Post MIC 2009 Volume). October 2009.

 

Joe Henry Obit, Dario Landa-Silva. Computational Study of Non-Linear Great Deluge for University Course Timetabling. To Appear in V. Sgurev, M. Hadjiski (eds). Intelligent Systems - From Theory to Practice. Post Conference IEEE-IS 2008 Volume, Series in Computational Intelligence, Springer Verlag, 2009.

 

Joe Henry Obit, Dario Landa-Silva, Djamilah Ouelhadj, Marc Sevaux. Non-Linear Great Deluge with Learning Mechanism for Solving the Course Timetabling Problem. In Proceedings of the 8th Metaheuristics International Conference (MIC 2009). July 2009

 

Dario Landa-Silva, Joe Henry Obit. Evolutionary Non-Linear Great Deluge for University Course Timetabling .  Accepted for publication in Proceedings of the 2009 International Conference on Hybrid Artificial Intelligence Systems (HAIS 2009), June 2009.

 

Dario Landa-Silva, Joe Henry Obit. Great Deluge with Nonlinear Decay Rate for Solving Course Timetabling Problems. Accepted for publication in Proceedings of the 2008 IEEE Conference on Intelligent Systems, September 2008.

 

 


Course Timetabling Problems Solutions (here)

 

Last updated Saturday, 12 November, 2009.

 

 

 

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