Edge Minimizing the Student Conflict Graph
This work addresses timetabling efficiency for schools, but it is incremental as it builds on existing sectioning and constraint programming methods.
The paper tackles the problem of assigning students to course sections to minimize potential scheduling conflicts, presenting a hybrid algorithm that combines greedy initialization with constraint programming to reduce edges in the student conflict graph, achieving a specific reduction in conflicts as applied to a constrained timetabling model.
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.