The Automation of Course Scheduling in Higher Education Institutions: Mathematical methods and software products
Abstract
The formation and management of schedules is repetitive and troublesome for any class, university and organization. Limited resources in terms of people, time and locations. Institutions needs solutions that will meet all of these constraints of scheduling. That system for scheduling should take in control the scheduling process which takes time by automatically allocating time slots for teaching and creating course schedule. And easily can be integrated with their systems without need to do some extra work like adding data for scheduling or exporting them, reducing the time spend on creating schedules and minimizing errors that made by people.Today, there are various types of systems and services designed to create schedules, reserve classrooms, assign classrooms for course teachers at specific times. The use of modern technologies, methods and models makes it easy to use open applications and services, as well as services at the local level. This paper presents the results of the analysis of systems. Their structures, algorithms, models, and also functional capabilities. The aim of this work is to determine the types of applications and systems, analysis of various options for the implementation of algorithms for the formation of schedules in educational institutions.Keywords: Automation, scheduling, time-tables, university, constraints, algorithmsReferences
1C Solutions, C. (2020, March 21). 1C : Company. Retrieved from 1C Solutions: https://solutions.1c.ru/catalog/asp_univer
Babkina, T. (2008). Scheduling: multi-agent approach solution. Business Informatics, 23-28.
Liviu, L., & Volker, D. (2020, April 7). FET. Retrieved from Free Timetabling Software: https://lalescu.ro/liviu/fet/credits.html
Müller, T., & Rudová, H. (2011). Proceedings of the 5th Multidisciplinary International Scheduling Conference. Rapid Development of University Course Timetables. MISTA.
Nikisha, K., & Marianthi, G. (2015). Lagrangian decomposition approach to scheduling large-scale refinery operations. Computers & Chemical Engineering, 1-29.
Ullman, J. D. (1973). NP-Complete Scheduling Problems. COMPUTER AND SYSTEM SCIENCES, 384-393.
University Timetabling. (2020, March 15). Retrieved from UniTime: https://www.unitime.org
Yong, O., & Yi, C. (2011). The 6th International Conference on Computer Science & Education. Design of automated Course Scheduling system based on hybrid genetic algorithm (pp. 256-259). Singapore: SuperStar Virgo.
Babkina, T. (2008). Scheduling: multi-agent approach solution. Business Informatics, 23-28.
Liviu, L., & Volker, D. (2020, April 7). FET. Retrieved from Free Timetabling Software: https://lalescu.ro/liviu/fet/credits.html
Müller, T., & Rudová, H. (2011). Proceedings of the 5th Multidisciplinary International Scheduling Conference. Rapid Development of University Course Timetables. MISTA.
Nikisha, K., & Marianthi, G. (2015). Lagrangian decomposition approach to scheduling large-scale refinery operations. Computers & Chemical Engineering, 1-29.
Ullman, J. D. (1973). NP-Complete Scheduling Problems. COMPUTER AND SYSTEM SCIENCES, 384-393.
University Timetabling. (2020, March 15). Retrieved from UniTime: https://www.unitime.org
Yong, O., & Yi, C. (2011). The 6th International Conference on Computer Science & Education. Design of automated Course Scheduling system based on hybrid genetic algorithm (pp. 256-259). Singapore: SuperStar Virgo.
Published
2020-06-08
How to Cite
RUSTAULETOV, Babur.
The Automation of Course Scheduling in Higher Education Institutions: Mathematical methods and software products.
Proceedings of International Young Scholars Workshop, [S.l.], v. 9, june 2020.
ISSN 2709-1120.
Available at: <https://journals.sdu.edu.kz/index.php/iysw/article/view/169>. Date accessed: 19 apr. 2025.
doi: https://doi.org/10.47344/iysw.v9i0.169.
Section
Articles