A tabu search algorithm with efficient diversification strategy for high school timetabling problem

TL;DR

This paper introduces a novel high school timetabling algorithm combining graph-based pre-scheduling, greedy heuristics, and tabu search with diversification, effectively producing acceptable timetables from real-world data.

Contribution

It presents a new multi-phase algorithm integrating graph methods, heuristics, and tabu search with diversification for high school timetabling.

Findings

Effective timetable generation for Iranian high schools

Algorithm outperforms traditional methods in quality and efficiency

Demonstrates robustness on real-world datasets

Abstract

The school timetabling problem can be described as scheduling a set of lessons (combination of classes, teachers, subjects and rooms) in a weekly timetable. This paper presents a novel way to generate timetables for high schools. The algorithm has three phases. Pre-scheduling, initial phase and optimization through tabu search. In the first phase, a graph based algorithm used to create groups of lessons to be scheduled simultaneously; then an initial solution is built by a sequential greedy heuristic. Finally, the solution is optimized using tabu search algorithm based on frequency based diversification. The algorithm has been tested on a set of real problems gathered from Iranian high schools. Experiments show that the proposed algorithm can effectively build acceptable timetables.