Course Scheduling in University using Agent Exploration in Timetable Media
Main Article Content
Abstract
Course scheduling in University is still a study area that is interesting for researchers to explore and search its optimization [4]. Scheduling optimization still depends on the needs of a University. Manual scheduling is still the most commonly used option, but it requires a skilled and expert person or person who has been accustomed to do so. However, the result still needs a lot of corrections. Course scheduling in College/University in Indonesia using semester credit system (SKS) is a challenge in making course schedule. Some scheduling methods have been proposed in several studies such as genetic methods [10], integer programming [1] and other methods using other agents [2] [7]. In the previous studies, the generated schedules must still be adjusted and or inflexible when there are changes in the schedule or its pattern, and its model cannot be applied to all Colleges/Universities in Indonesia using semester credit system (SKS). This study offers a method which is referring to the constrains/conditions in Universities but still flexible in its formation and change. Agent will explore timetable media to locate time cell/slot corresponding to the scheduling using credit system (SKS).
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
IJCERT Policy:
The published work presented in this paper is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This means that the content of this paper can be shared, copied, and redistributed in any medium or format, as long as the original author is properly attributed. Additionally, any derivative works based on this paper must also be licensed under the same terms. This licensing agreement allows for broad dissemination and use of the work while maintaining the author's rights and recognition.
By submitting this paper to IJCERT, the author(s) agree to these licensing terms and confirm that the work is original and does not infringe on any third-party copyright or intellectual property rights.
References
Bakir, M.A and Askop, C, “A 1-0 Integer Programming Approach to a UniversityTimetabling Problem”, Hecettepe Juornal of Mathematics and Statistics, Vol 37(1), pp. 41-55, 2008.
El-Helly, M., Abdelhamid, Y. dan Al-Wakeel, M.,”A Multi-Agent Pattern Based Timetabling System”, EgyptianComputer Science Journal,Vol. 35, No. 3 September 2011
Glascheko, A., Ivaschenko, A., Rzevski, G. dan Skobelev, P., “Multi-Agent Real Time Scheduling for Taxi Companies”, 8th International Conference on Autonomous Agents and Multiagent Systems,10-15 may 2009, Budapest, Hungaria.
Hakim, J and Wardoyo, R.,”Using Grid for Course Scheduling with Multi Agent”, International seminar of Information Technologi (ISIT), October 23th, 2010, Bandung, pp 147-149.
Hosny, M. and Fatimah,S.,”A Survey of Genetic Algoritms for University Timetabling Problem”, International Conference on Future Information Technology,IPCSIT vol. 13 (2011) IACSIT Press, Singapore
Hutzschenreuter, A. K., Bosman, P. A. N. dan Blonk-Altena, I.,”Agent-based Anmission scheduling in Hospital”, 7th International Conference on Autonomous and Multiagent System (AAMS 2008),pp 45-52, Estoril, Portugal
Mehmood, T. dan Farid, M. S.”A Multi-agent Architecture for Task Scheduling In University Environment”, IAES International Juornal of Artificial Intelligent,Vol. 1, No. 4, Des 2012, pp. 193-200, ISSN:2252-8938.
Paulo, R. dan Rocco, P., “Adaptive Dynamic Scheduling in Agent Based Manufacturing Environment : A Budget Approach”, Communication of IBIMA, Volume 7, 2009 ISSN : 1943-7765
Russell, S. and Norvig, P.,“Artificial Intelligence: A Modern Approach”, 2nd ed. Prentice Hall. 2003, New Jersey, USA.
Suryadi, D. and Philipus, R.”Genetic Algorithm For University Timetable Planning in FTI”, Proceeding of the 2012 International Conference and Industrial Engineering Operation Management, , July 3-6, 2012, Istambul, Turkey