A hybrid algorithm for the university course timetabling problem using the improved parallel genetic algorithm and local search
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-020-01833-x.pdf
Reference75 articles.
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2. Abuhamdah A, Ayob M, Kendall G, Sabar NR (2014) Population based local search for university course timetabling problems. Appl Intell 40(1):44–53. https://doi.org/10.1007/s10489-013-0444-6
3. Thepphakorn T, Pongcharoen P (2019) Variants and parameters investigations of particle swarm optimisation for solving course timetabling problems. In: International conference on swarm intelligence. Springer, Cham, pp 177–187. https://doi.org/10.1007/978-3-030-26369-0_17
4. Bashab A, Ibrahim AO, AbedElgabar EE, Ismail MA, Elsafi A, Ahmed A, Abraham A (2020) A systematic mapping study on solving university timetabling problems using meta-heuristic algorithms. Neural Comput & Applic 32(11):1–36. https://doi.org/10.1007/s00521-020-05110-3
5. Pintér M, Dávid B (2019) A two-stage heuristic for the university course timetabling problem. In: Proceedings of the 2019 6th student computer science research conference-StuCoSReC. Univerza na Primorskem, Inštitut Andrej Marušič, pp 27–30. https://doi.org/10.26493/978-961-7055-82-5.27-30
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