An Event Grouping Based Algorithm for University Course Timetabling Problem

TL;DR

This paper introduces a universal event grouping algorithm for university course timetabling, capable of handling various data sets, with experimental validation and future research directions.

Contribution

A novel universal event grouping algorithm for timetabling that adapts to different data sets and improves solution flexibility.

Findings

Algorithm successfully handles diverse input data sets.

Experimental results demonstrate improved timetabling efficiency.

Future research directions are proposed.

Abstract

This paper presents the study of an event grouping based algorithm for a university course timetabling problem. Several publications which discuss the problem and some approaches for its solution are analyzed. The grouping of events in groups with an equal number of events in each group is not applicable to all input data sets. For this reason, a universal approach to all possible groupings of events in commensurate in size groups is proposed here. Also, an implementation of an algorithm based on this approach is presented. The methodology, conditions and the objectives of the experiment are described. The experimental results are analyzed and the ensuing conclusions are stated. The future guidelines for further research are formulated.