Solving the exam timetabling problem via a multi-objective evolutionary algorithm - A more general approach

C. Y. Cheong; K. C. Tan; B. Veeravalli

doi:10.1109/SCIS.2007.367685

Solving the exam timetabling problem via a multi-objective evolutionary algorithm - A more general approach

C. Y. Cheong
, K. C. Tan
, B. Veeravalli

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

13 Citations (Scopus)

Abstract

This paper studies a multi-objective instance of the university exam timetabling problem. On top of satisfying universal hard constraints such as seating capacity and no overlapping exams, the solution to this problem requires the minimization of the timetable length as well as the number of occurrences of students having to take exams in consecutive periods within the same day. While most existing approaches to the problem, as well as the more popular single-objective instance, require prior knowledge of the desired timetable length, the multi-objective evolutionary algorithm proposed in this paper is able to generate feasible solutions even without the information. The effectiveness of the proposed algorithm is benchmarked against a few recent and established optimization techniques and is found to perform well in comparison. © 2007 IEEE.

Original language	English
Title of host publication	2007 IEEE Symposium on Computational Intelligence in Scheduling
Publisher	IEEE
Pages	165-172
ISBN (Print)	1-4244-0704-4
DOIs	https://doi.org/10.1109/SCIS.2007.367685
Publication status	Published - Apr 2007
Externally published	Yes
Event	2007 IEEE Symposium on Computational Intelligence in Scheduling (CI-Sched 2007) - Honolulu, United States Duration: 1 Apr 2007 → 5 Apr 2007

Conference

Conference	2007 IEEE Symposium on Computational Intelligence in Scheduling (CI-Sched 2007)
Place	United States
City	Honolulu
Period	1/04/07 → 5/04/07

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@inproceedings{cf97ef58c257414780d6eb91b97417f0,

title = "Solving the exam timetabling problem via a multi-objective evolutionary algorithm - A more general approach",

abstract = "This paper studies a multi-objective instance of the university exam timetabling problem. On top of satisfying universal hard constraints such as seating capacity and no overlapping exams, the solution to this problem requires the minimization of the timetable length as well as the number of occurrences of students having to take exams in consecutive periods within the same day. While most existing approaches to the problem, as well as the more popular single-objective instance, require prior knowledge of the desired timetable length, the multi-objective evolutionary algorithm proposed in this paper is able to generate feasible solutions even without the information. The effectiveness of the proposed algorithm is benchmarked against a few recent and established optimization techniques and is found to perform well in comparison. {\textcopyright} 2007 IEEE.",

author = "Cheong, \{C. Y.\} and Tan, \{K. C.\} and B. Veeravalli",

year = "2007",

month = apr,

doi = "10.1109/SCIS.2007.367685",

language = "English",

isbn = "1-4244-0704-4",

pages = "165--172",

booktitle = "2007 IEEE Symposium on Computational Intelligence in Scheduling",

publisher = "IEEE",

address = "United States",

note = "2007 IEEE Symposium on Computational Intelligence in Scheduling (CI-Sched 2007) ; Conference date: 01-04-2007 Through 05-04-2007",

}

Cheong, CY, Tan, KC & Veeravalli, B 2007, Solving the exam timetabling problem via a multi-objective evolutionary algorithm - A more general approach. in 2007 IEEE Symposium on Computational Intelligence in Scheduling., 4218612, IEEE, pp. 165-172, 2007 IEEE Symposium on Computational Intelligence in Scheduling (CI-Sched 2007), Honolulu, Hawaii, United States, 1/04/07. https://doi.org/10.1109/SCIS.2007.367685

Solving the exam timetabling problem via a multi-objective evolutionary algorithm - A more general approach. / Cheong, C. Y.; Tan, K. C.; Veeravalli, B.
2007 IEEE Symposium on Computational Intelligence in Scheduling. IEEE, 2007. p. 165-172 4218612.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Solving the exam timetabling problem via a multi-objective evolutionary algorithm - A more general approach

AU - Cheong, C. Y.

AU - Tan, K. C.

AU - Veeravalli, B.

PY - 2007/4

Y1 - 2007/4

N2 - This paper studies a multi-objective instance of the university exam timetabling problem. On top of satisfying universal hard constraints such as seating capacity and no overlapping exams, the solution to this problem requires the minimization of the timetable length as well as the number of occurrences of students having to take exams in consecutive periods within the same day. While most existing approaches to the problem, as well as the more popular single-objective instance, require prior knowledge of the desired timetable length, the multi-objective evolutionary algorithm proposed in this paper is able to generate feasible solutions even without the information. The effectiveness of the proposed algorithm is benchmarked against a few recent and established optimization techniques and is found to perform well in comparison. © 2007 IEEE.

AB - This paper studies a multi-objective instance of the university exam timetabling problem. On top of satisfying universal hard constraints such as seating capacity and no overlapping exams, the solution to this problem requires the minimization of the timetable length as well as the number of occurrences of students having to take exams in consecutive periods within the same day. While most existing approaches to the problem, as well as the more popular single-objective instance, require prior knowledge of the desired timetable length, the multi-objective evolutionary algorithm proposed in this paper is able to generate feasible solutions even without the information. The effectiveness of the proposed algorithm is benchmarked against a few recent and established optimization techniques and is found to perform well in comparison. © 2007 IEEE.

UR - https://www.scopus.com/pages/publications/34548804847

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DO - 10.1109/SCIS.2007.367685

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SN - 1-4244-0704-4

SP - 165

EP - 172

BT - 2007 IEEE Symposium on Computational Intelligence in Scheduling

PB - IEEE

T2 - 2007 IEEE Symposium on Computational Intelligence in Scheduling (CI-Sched 2007)

Y2 - 1 April 2007 through 5 April 2007

ER -

Solving the exam timetabling problem via a multi-objective evolutionary algorithm - A more general approach

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