Call for Paper

CAE solicits original research papers for the April 2019 Edition. Last date of manuscript submission is March 30, 2019.

Read More

Development of Mechanism for Handling Conflicts and Constraints in University Timetable Management System

Constance Kalu, Simeon Ozuomba, Sylvester Isreal Umana. Published in Information Systems.

Communications on Applied Electronics
Year of Publication: 2018
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Constance Kalu, Simeon Ozuomba, Sylvester Isreal Umana
10.5120/cae2018652804

Constance Kalu, Simeon Ozuomba and Sylvester Isreal Umana. Development of Mechanism for Handling Conflicts and Constraints in University Timetable Management System. Communications on Applied Electronics 7(24):22-32, December 2018. BibTeX

@article{10.5120/cae2018652804,
	author = {Constance Kalu and Simeon Ozuomba and Sylvester Isreal Umana},
	title = {Development of Mechanism for Handling Conflicts and Constraints in University Timetable Management System},
	journal = {Communications on Applied Electronics},
	issue_date = {December 2018},
	volume = {7},
	number = {24},
	month = {Dec},
	year = {2018},
	issn = {2394-4714},
	pages = {22-32},
	numpages = {11},
	url = {http://www.caeaccess.org/archives/volume7/number24/842-2018652804},
	doi = {10.5120/cae2018652804},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

In this paper development of mechanism for handling conflicts and constraints in university timetable management system is presented. The mechanism consists of a set of algorithms and analytical expressions for resolving conflicts and managing constraints in the university timetable scheduling system. In order to handle conflicts associated with courses, the courses are ranked based on their total ranking scores (TRS). In order to handle conflicts associated with course lecturers, the lecturers are ranked based on their ranking weight (W). Provision is also made to accommodate students’ activities constraints. The venues are first matched with the courses based on their carrying capacity which is enough to accommodate the class size. Then the procedure for time allocation to courses on the timetable considers the course ranking first before the lecturers ranking. In all, the design constraints and decisions were based on information on the timetable issues at University of Uyo, Akwa Ibom state, Nigeria. The mechanism was used in a proof of concept web-based timetable management system for University of Uyo and with the sample data used to test the system there was no observed conflict in the timetable. Though the present mechanism for automating timetable conflict resolution is tailored towards University of Uyo as the case study, the idea presented can be adapted or further developed and generalized to apply to other institutions.

References

  1. Oke, T. I., & Bukar, I. B. (2018). Exploring Alternative Sources of Funding Universal Basic Education for Sustainable Development in Nigeria. KIU Journal of Humanities, 2(2 (A)), 31-38.
  2. Twumasi-Ampofo, K., Ofori, P. A., Tutu, E. O., Cobinah, R., Twumasi, E. A., & Kusi, S. (2017). Maintenance of government buildings in Ghana: the case of selected public residential buildings in Ejisu-Ashanti. Journal of Emerging Trends in Economics and Management Sciences (JETEMS), 8(3), 146-154.
  3. Oluwatumbi, O. S., & Olubunmi, A. V. (2017). Availability And Utilization Of Internet Facilities Among Undergraduate Students Of Colleges Of Education Nigeria. British Journal of Education, 5(9), 100-107.
  4. Vrielink, R. O., Jansen, E. A., Hans, E. W., & van Hillegersberg, J. (2017). Practices in timetabling in higher education institutions: a systematic review. Annals of Operations Research, 1-16.
  5. Ansari, A., & Bojewar, S. (2014). Genetic Algorithm to Generate the Automatic Time-Table–An Over View. International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), 2(11), 3480-3483.
  6. Pillay, N. (2012). Hyper-heuristics for educational timetabling. In Proceedings of the 9th International Conference on the Practice and Theory of Automated Timetabling (pp. 316-340).
  7. Sutar, S. R., & Bichkar, R. S. (2012). University timetabling based on hard constraints using genetic algorithm. International Journal of Computer Applications, 42(15), 3-5.
  8. Petrovic, S., & Burke, E. K. (2004). Educational timetabling. Handbook of scheduling: algorithms, models, and performance analysis, 45-1.
  9. Vrielink, R. O., Jansen, E. A., Hans, E. W., & van Hillegersberg, J. (2017). Practices in timetabling in higher education institutions: a systematic review. Annals of Operations Research, 1-16.
  10. Ansari, A., & Bojewar, S. (2014). Genetic Algorithm to Generate the Automatic Time-Table–An Over View. International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), 2(11), 3480-3483.
  11. Pillay, N. (2012). Hyper-heuristics for educational timetabling. In Proceedings of the 9th International Conference on the Practice and Theory of Automated Timetabling (pp. 316-340).
  12. Sutar, S. R., & Bichkar, R. S. (2012). University timetabling based on hard constraints using genetic algorithm. International Journal of Computer Applications, 42(15), 3-5.
  13. Petrovic, S., & Burke, E. K. (2004). Educational timetabling. Handbook of scheduling: algorithms, models, and performance analysis, 45-1.
  14. Ugwu, O. O., Okafor, C. C., & Nwoji, C. U. (2018). Assessment of building maintenance in Nigerian university system: a case study of University of Nigeria, Nsukka. Nigerian Journal of Technology, 37(1), 44-52.
  15. Eze, S. C., Chinedu-Eze, V. C., & Bello, A. O. (2018). The utilisation of e-learning facilities in the educational delivery system of Nigeria: a study of M-University. International Journal of Educational Technology in Higher Education, 15(1), 34.
  16. Udidai, U. J., Essien, E. S., & Pisca, J. I. (2017). Institutional Activities and Accreditation of Higher Education Academic Programmes in the Era of Economic Recession in Cross River State, Nigeria.
  17. Akinkunmi, T. (2016). Assessment of Maintenance Management Culture of Tertiary Institutions in Nigeria. Assessment, 8(6).
  18. Hénard, F., & Roseveare, D. (2012). Fostering quality teaching in higher education: Policies and Practices. An IMHE Guide for Higher Education Institutions, 7-11.
  19. Vandiver, B. (2011). The impact of school facilities on the learning environment. Capella University.
  20. Henard, F., & Leprince-Ringuet, S. (2008). The path to quality teaching in higher education. Paris: OCED Publication.–2008.
  21. Bullock, C. (2007). The relationship between school building conditions and student achievement at the middle school level in the Commonwealth of Virginia (Doctoral dissertation, Virginia Tech).
  22. Lin, Y. P., Chang, T. K., Fan, C., Anthony, J., Petway, J. R., Lien, W. Y., ... & Ho, Y. F. (2017). Applications of information and communication technology for improvements of water and soil monitoring and assessments in agricultural areas—A case study in the Taoyuan irrigation district. Environments, 4(1), 6.
  23. Oyier, C. R., Odundo, P. A., Lilian, G. K., & Wangui, K. R. (2015). Effects of ICT Integration in Management of Private Secondary Schools in Nairobi County, Kenya: Policy Options and Practices. World Journal of Education, 5(6), 14.
  24. Forcada Matheu, N. (2005). Life cycle document management system for construction. Universitat Politècnica de Catalunya.
  25. Berkhout, F., & Hertin, J. (2001). Impacts of information and communication technologies on environmental sustainability: Speculations and evidence. Report to the OECD, Brighton, 21.
  26. Ramos, A. L. A., Matienzo, K. L. C., Casunuran, J. M. D., Nervida, C. M., Rosal, J. M. S., & Bederico, A. V. (2018). E-Vision: A Campus Locator Map Mobile Application using A* Algorithm. International Journal of Computer Science and Software Engineering, 7(1), 6-11.
  27. Kulkarni, K. R., Yatish, C. H., Kamble, K. P., Kulkarni, A. A., & Bangi, S. C. (2017). Development of 2D Map and 3D Model of GIT Campus using GIS Technology.
  28. Hall, C. S. J. S., & Hall, D. S. G. S. (2017). Campus map. Lamp, 99, 1.
  29. Chowdhary, A., Kakde, P., Dhoke, S., Ingle, S., Rushiya, R., & Gawande, D. (2014). Timetable Generation System. International Journal of Computer Science and Mobile Computing, 3(2).
  30. Doulaty, M., Derakhshi, M. F., & Abdi, M. (2013). Timetabling: A state-of-the-art evolutionary approach. International Journal of Machine Learning and Computing, 3(3), 255.
  31. Murray, K., & Müller, T. (2006). Automated System for University Timetabling. In Proceedings of the 6 th International Conference on the Practice and Theory of Automated Timetabling (pp. 536-541).
  32. Smith, S. F. (2005). Is scheduling a solved problem?. In Multidisciplinary Scheduling: Theory and Applications (pp. 3-17). Springer, Boston, MA.
  33. Chand, A. (2004). A constraint based generic model for representing complete university timetabling data. In Proceedings of the 5th International Conference on the Practice and Theory of Automated Timetabling (pp. 125-150).

Keywords

Timetable, Venue Constraint, Map Mashup, Spatial Information System