<![CDATA[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 ]]>
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