An Optimization Approach to the Make-Up Final Exam Scheduling Problem with Unique Constraints
DOI:
https://doi.org/10.37266/ISER.2020v8i1.pp50-58Keywords:
Scheduling, University, Optimization, Unique Constraints, United States Air Force Academy, Final ExamAbstract
Final exam scheduling is typically a simple task. Exam scheduling at the United States Air Force Academy, however, is unique in that it must abide by a number of institutional constraints. Some include: ensuring all 4,000 cadets complete their exams within one week, assigning a longer time block for final exams than regular class meetings, and limiting the number of exam periods per day. The Dean of Faculty Registrar’s office must also accommodate cadet absences during the scheduled final exam week on short notice. Addressing these issues is currently a reactive process—cadet absences are identified, and then the Registrar creates adjusted schedules by hand. In this study, we create a data-cleaning VBA module for input data and use Xpress software to execute one of three versions of a scheduling optimization model. The model reduces the scheduling task time from several days to less than five minutes.References
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Zhaohui, F., & Lim, A. (n.d.). Heuristics for the exam scheduling problem. Proceedings 12th IEEE Internationals Conference on Tools with Artificial Intelligence. ICTAI 2000. 172-175.
Carter, M. W. (1986). OR practice—a survey of practical applications of examination timetabling algorithms. Operations Research, 34(2), 193-202.
Dimopoulou, M., & Miliotis, P. (2001). Implementation of a University Course and Examination Timetabling System. European Journal of Operational Research, 130(1), 202-213.
Guadagno, K., Saval, K., Van Drew, Q., Vasiliadis, S., Cho, P., & Pietz, J. (2015). Optimizing Humanitarian Relief Operations with Transloads. Industrial and Systems Engineering Review, 3(2), 98-106. Retrieved from http://watsonojs.binghamton.edu/index.php/iser/article/view/44
Goulas, S., & Megalokonomou, R. (2020). Marathon, Hurdling or Sprint? The Effects of Exam Scheduling on Academic Performance. The B.E. Journal of Economic Analysis and Policy, 20(2), 1-36.
Lotfi, V., & Cerveny, R. (1991). A Final-Exam-Scheduling Package. Journal of the Operational Research Society, 42(3), 205-216.
Qu, R., & Burke, E. (2009). Hybridizations within a Graph-Based Hyper-Heuristic Framework for University Timetabling Problems. The Journal of the Operational Research Society, 60(9), 1273-1285.
Romero, B. (1982). Examination Scheduling in a Large Engineering School: A Computer-Assisted Participative Procedure. Interfaces, 12(2), 17-24.
Sampson, S., Freeland, J., & Weiss, E. (1995). Class Scheduling to Maximize Participant Satisfaction. Interfaces, 25(3), 30-41.
Singh, E., Joshi, V. D., & Gupta, N. (2008) Optimizing highly constrained examination time tabling problems. Journal of Applied Mathematics, Statistics and Informatics. (JAMSI), 4 (2008), No. 2.
Wong, T., Côté, P., & Gely, P. (2002, May). Final exam timetabling: a practical approach. IEEE CCECE2002. Canadian Conference on Electrical and Computer Engineering. Conference Proceedings (Cat. No. 02CH37373), Winnipeg, Manitoba, Canada (Vol. 2, pp. 726-731). IEEE.
Zhaohui, F., & Lim, A. (n.d.). Heuristics for the exam scheduling problem. Proceedings 12th IEEE Internationals Conference on Tools with Artificial Intelligence. ICTAI 2000. 172-175.
Published
2021-03-06
How to Cite
Blanks, L., Frakes, E., Hinnant, K., Samuel, S., & Dulin, J. (2021). An Optimization Approach to the Make-Up Final Exam Scheduling Problem with Unique Constraints. Industrial and Systems Engineering Review, 8(1), 50-58. https://doi.org/10.37266/ISER.2020v8i1.pp50-58
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