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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 10, 2022.
Abstract: Generating university course timetables is a complex problem, especially in large environments such as institutions. Currently, some universities in Saudi Arabia manually generate timetables for classes because they use Vendor Management Systems (VMS) for registration and management. Manually generating course timetables is time-consuming and laborious for the academic staff. Although various methods have been proposed to generate timetables, they address specific environments or systems that can be extended to or work as separate components of the university management system. In this paper, we propose a service-based system with a decentralized architecture that can fully automate the process of course timetable generation and can be easily integrated into VMS. The proposed service-based system employs a genetic algorithm to optimize the process of scheduling courses and generating timetables. The system was implemented using JAVA RESTful web services, and the algorithm was tested by generating various course timetables with various constraints. The results showed that the proposed decentralized architecture is applicable to and can be fully integrated with any VMS. Furthermore, the use of genetic algorithm set up to 200 generations and iterate 1000 times produces acceptable timetables without violating any of the defined constraints.
Marwah M. Alansari, “Optimized Automatic Course Timetabling Service Architecture for Integration with Vendor Management Systems” International Journal of Advanced Computer Science and Applications(IJACSA), 13(10), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01310104
@article{Alansari2022,
title = {Optimized Automatic Course Timetabling Service Architecture for Integration with Vendor Management Systems},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01310104},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01310104},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {10},
author = {Marwah M. Alansari}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.