Benchmarking a standard genetic algorithm for real-world university class timetabling

Yousef Farhang; Saman Tarighpeyma Aghbolagh; Ülker Başar

doi:10.61112/jiens.1829317

Benchmarking a standard genetic algorithm for real-world university class timetabling

Abstract

The university class timetabling is known to be a classic example of a problem in combinatorial optimization, where an allocation of classes to time periods, classrooms, and tutors is needed. Although modern works mostly concentrate on designing various hybrid or specialized algorithms and metaheuristics, one should also examine the performance of the original algorithm to obtain a baseline metric for future comparisons. This paper considers a simple application of the unaltered SGA on Dataset A that has 38 subjects, 8 tutors, 8 classrooms, five days of operation, and two types of classes (theoretical and practical). As far as scalability was concerned, we have tested several population sizes for the algorithm, namely 15, 30, 60, and 120. Performance metrics such as fitness and the rate of convergence were measured according to the value of the fitness function and runtime as well as memory usage. It could be demonstrated that despite being extremely simple, classical SGA produces valid solutions for this problem but is quite sensitive to changes in population size. To make the analysis more robust, the paper also includes a very basic comparison experiment involving Simulated Annealing as another basis of evaluation.

Keywords

Project Number

0

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Details

Primary Language

English

Subjects

Computer Software

Journal Section

Research Article

Authors

Yousef Farhang ^*
0000-0001-9348-2624
Türkiye

Saman Tarighpeyma Aghbolagh
0009-0002-6919-0570
Türkiye

Ülker Başar
0009-0000-6720-4161
Türkiye

Publication Date

July 30, 2026

Submission Date

November 24, 2025

Acceptance Date

July 15, 2026

Published in Issue

Year 2026 Volume: 6 Number: 2

DOI

https://doi.org/10.61112/jiens.1829317

IZ

https://izlik.org/JA27ZF74AR

Cite

RIS / Bibtex

APA

Farhang, Y., Tarighpeyma Aghbolagh, S., & Başar, Ü. (2026). Benchmarking a standard genetic algorithm for real-world university class timetabling. Journal of Innovative Engineering and Natural Science, 6(2), 502-513. https://doi.org/10.61112/jiens.1829317

AMA

1.Farhang Y, Tarighpeyma Aghbolagh S, Başar Ü. Benchmarking a standard genetic algorithm for real-world university class timetabling. JIENS. 2026;6(2):502-513. doi:10.61112/jiens.1829317

Chicago

Farhang, Yousef, Saman Tarighpeyma Aghbolagh, and Ülker Başar. 2026. “Benchmarking a Standard Genetic Algorithm for Real-World University Class Timetabling”. Journal of Innovative Engineering and Natural Science 6 (2): 502-13. https://doi.org/10.61112/jiens.1829317.

EndNote

Farhang Y, Tarighpeyma Aghbolagh S, Başar Ü (July 1, 2026) Benchmarking a standard genetic algorithm for real-world university class timetabling. Journal of Innovative Engineering and Natural Science 6 2 502–513.

IEEE

[1]Y. Farhang, S. Tarighpeyma Aghbolagh, and Ü. Başar, “Benchmarking a standard genetic algorithm for real-world university class timetabling”, JIENS, vol. 6, no. 2, pp. 502–513, July 2026, doi: 10.61112/jiens.1829317.

ISNAD

Farhang, Yousef - Tarighpeyma Aghbolagh, Saman - Başar, Ülker. “Benchmarking a Standard Genetic Algorithm for Real-World University Class Timetabling”. Journal of Innovative Engineering and Natural Science 6/2 (July 1, 2026): 502-513. https://doi.org/10.61112/jiens.1829317.

JAMA

1.Farhang Y, Tarighpeyma Aghbolagh S, Başar Ü. Benchmarking a standard genetic algorithm for real-world university class timetabling. JIENS. 2026;6:502–513.

MLA

Farhang, Yousef, et al. “Benchmarking a Standard Genetic Algorithm for Real-World University Class Timetabling”. Journal of Innovative Engineering and Natural Science, vol. 6, no. 2, July 2026, pp. 502-13, doi:10.61112/jiens.1829317.

Vancouver

1.Yousef Farhang, Saman Tarighpeyma Aghbolagh, Ülker Başar. Benchmarking a standard genetic algorithm for real-world university class timetabling. JIENS. 2026 Jul. 1;6(2):502-13. doi:10.61112/jiens.1829317