Abstract
With the university expansion, how to maintain teaching order using limited resources make the intelligent course scheduling become a multiple-constraint and multi-objective optimization problem. Traditional intelligent course scheduling algorithm is inefficient, cannot solve curriculum conflict question and meet the requirements of the modern university education management. Given this situation, this paper analyzes the university timetabling problem, and establishes a general course scheduling model; then proposes an improved genetic algorithm to sovle the intelligent course scheduling problem. It can meet all of the education resources’ constraints and the teachers’ personal demands as much as possible. Test the performance of between the improved genetic algorithm and simple genetic algorithm under different scenarios, the experimental results show that the improved genetic algorithm has better performance, can schedule courses reasonable. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4798
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: TELKOMNIKA Indonesian Journal of Electrical Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
