MODELLING AND OPTIMIZATION OF THE EXAM INVIGILATOR ASSIGNMENT PROBLEM BASED ON PREFERENCES

Abstract

The assignment process of invigilators to the exams could be difficult and time-consuming process when there are too many exam centers and the invigilator who will assign. In particular, due to the constraints of assignment according to the characteristics of the invigilators, keeping the assignment process taking into account the officer's preferences and the fact that the test centers have a certain capacity makes the problem very complicated. In this study, the situation was considered as an assignment problem. To solve this complicated situation, we formulated the problem, with the constraints of the capacity of exam centers, type of the invigilator, type of centers and other restrictions. An algorithm for model implementation was developed and automation suitable to the algorithm was written in C# language. The model was then applied to the case of exam invigilators assignment at Open Distance Faculty of Anadolu University. All the assignment process time is reduced from weeks to several minutes. 

Keywords

• Examiner Assignment Problem
• Optimization
• Mathematical Modeling
• Automated assignment systems

References

1. Burkard, R. E. (2002). "Selected topics on assignment problems." Discrete Applied Mathematics 123(1-3): 257-302.
2. Diaz, E. F. v. J. (2001). "A Tabu Search Heuristic for the generalized assignment problem." Europian Journal of Operational Research 132: 22-28.
3. Elizondo, R. (1994). Solving very large scale school/student assignment problems, Rice University.
4. Elloumi, A., et al. (2014). "The classroom assignment problem: Complexity, size reduction and heuristics." Applied Soft Computing 14: 677-686.
5. G. Liu, S. W., Y. Zhang (2011). "New Prediction Algorithm for English Class Personnel Assignment Problem." Advances in Computer Science, Intelligent System and Environment 104: 95-98.
6. Hanum, F., et al. (2015). "Exam invigilators assignment problem: a goal programming approach." Applied Mathematical Sciences 9(58): 2871-2880.
7. Hojati, M. (2010). "Near-optimal solution to an employee assignment problem with seniority." Annals of Operations Research 181(1): 539-557.
8. K.Bhunia, J. M. v. A. (2010). "Penalty approaches for Assignment Problem with single side constraint via Genetic Algorithms." Journal of Mathematical Modelling and Application 2(2): 60-86.

9. Karimzadehgan, M. and C. X. Zhai (2012). "Integer linear programming for Constrained Multi-Aspect Committee Review Assignment." Information Processing & Management 48(4): 725-740.
10. Liang, B. and A. Turkcan (2016). "Acuity-based nurse assignment and patient scheduling in oncology clinics." Health care management science 19(3): 207-226.
11. Loiola, E. M., et al. (2007). "A survey for the quadratic assignment problem." European Journal of Operational Research 176(2): 657-690.
12. Oncan, T. (2007). "A survey of the generalized assignment problem and its applications." Infor 45(3): 123-141.
13. Özener, O. Ö., et al. (2017). "Solving a large-scale integrated fleet assignment and crew pairing problem." Annals of Operations Research 253(1): 477-500.
14. P. Tapkan, L. Ö. v. A. B. (2008). "Arı Algoritması ve Genelleştirilmiş Atama Problemi: Farklı Komşuluk Yapılarının Karşılaştırılması." Endüstri Mühendisliði Dergisi 21(2): 2-13.
15. Patriksson, M. (2015). The traffic assignment problem: models and methods, Courier Dover Publications.
16. Pentico, D. W. (2007). "Assignment problems: A golden anniversary survey." European Journal of Operational Research 176(2): 774-793.
17. Poole, A. and A. Kotsialos (2016). "Swarm intelligence algorithms for macroscopic traffic flow model validation with automatic assignment of fundamental diagrams." Applied Soft Computing 38: 134-150.
18. Subramanian, R., et al. (1994). "Coldstart: fleet assignment at Delta Air Lines." Interfaces 24(1): 104-120.
19. Wang, Z., et al. (2017). "The ABCD patient classification tool for nurse-to-patient assignment to improve nursing workload balance: a multi-center study." International Journal of Clinical And Experimental Medicine 10(6): 9502-9507.