Using a genetic algorithm optimizer tool to generate good quality timetables

This paper describes a Genetic Algorithm optimizer tool with adaptive parameter control designed to generate a university timetable. In this research we aim to show that by controlling the parameter settings of the genetic operators we can improve the quality of the timetable. This tool was tested on actual data and we present the experimental results.