Edge Minimizing the Student Conflict Graph

TL;DR

This paper introduces a hybrid algorithm combining greedy and constraint programming techniques to minimize student conflicts in course timetabling by reducing edges in the conflict graph.

Contribution

It presents a novel hybrid approach that effectively minimizes student conflicts in timetabling through a combination of greedy and CP-SAT algorithms.

Findings

The hybrid algorithm reduces the number of conflicts compared to baseline methods.

Application to a highly constrained model demonstrates improved conflict minimization.

The approach is effective in practical timetabling scenarios.

Abstract

In many schools, courses are given in sections. Prior to timetabling students need to be assigned to individual sections. We give a hybrid approximation sectioning algorithm that minimizes the number of edges (potential conflicts) in the student conflict graph (SCG). We start with a greedy algorithm to obtain a starting solution and then continue with a constraint programming based algorithm (CP-SAT) that reduces the number of edges. We apply the sectioning algorithm to a highly constrained timetabling model which we specify.