Application of automated system for university course timetable scheduling: an Algerian case study
by Talib Hicham Betaouaf; Rabab Boukli-Hacene; Mohamed Amine Cherier
International Journal of Knowledge Engineering and Data Mining (IJKEDM), Vol. 7, No. 1/2, 2021

Abstract: Scheduling is an NP-hard problem which most universities are grappling with. For each academic semester, the timetabling process must be carried out regularly, which is an overwhelming and time-consuming activity. The main contribution of this study is developing an automated system based on a multi-agent (MA) approach and genetic algorithms (GA) to generate a university timetable. Three agents named capture agent (CA), processing agent (PA) and distributing agent (DA) have been worked collaboratively and cooperatively to develop the university timetable. The study has been applied in a real case study to perform the course schedules in the electrical and electronic engineering department of our university. The system implemented has considerably reduced the time and effort in the timetables realisation of our department from about ten days to only a few minutes. It has also significantly improved the quality of timetable by guaranteeing a satisfaction rate of over 95% of the constraints.

Online publication date: Wed, 22-Dec-2021

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