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3018. StudyPlanner: Helping students to plan university courses with integer programming

Invited abstract in session WB-37: Discrete Multiobjective Optimization, stream Multiobjective Optimization.

Wednesday, 10:30-12:00
Room: 33 (building: 306)

Authors (first author is the speaker)

1. Andreas Wiese
Mathematics, Technical University of Munich
2. Michael Ritter
Department of Mathematics, Technical University of Munich
3. Philipp Wiedmann
Department of Mathematics, Technical University of Munich

Abstract

At the beginning of each semester, all university students need to plan the courses they want to take this semester. In the process, they need to take into account the rules of their degree program. Those might, for example, regulate that some courses are compulsory, that one needs to complete a certain number of credits from a group of courses, or that one needs to choose a study focus from some given options. Also, there are additional considerations, such as the preferences of the student for certain subjects, the times when the courses are scheduled, or that some courses need to be taken in a certain order. In particular, it is a good idea to not just plan the courses of the upcoming semester, but all courses in all future semesters.

This leads to an optimization problem with multiple objectives that include, for example, minimizing the time until graduation and maximizing the satisfaction of the student with the selected courses. We propose an integer programming (IP) formulation for this problem and apply it to the Bachelor and Master degree in Mathematics at the Technical University of Munich (TUM). In our computational experiments, we could solve most of the tested instances in about one second using the non-commercial IP solver SCIP, and even faster with Gurobi. We made our planning tool available to the students of the Department of Mathematics at TUM. It is publicly accessible at https://studyplanner.co.cit.tum.de.

Keywords

Status: accepted


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