Title :
Using a genetic algorithm optimizer tool to generate good quality timetables
Author :
El Mahdi, Omar ; Ainon, R.N. ; Zainuddin, Roziati
Author_Institution :
Fac. of Comput. Sci. & Inf. Technol., Malaya Univ., Kuala Lumpur, Malaysia
Abstract :
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.
Keywords :
educational administrative data processing; further education; genetic algorithms; graph colouring; scheduling; adaptive parameter control; constrained scheduling problems; fitness function; genetic algorithm optimizer tool; good quality timetables; graph colouring; lecture timetable; parameter settings; repair function; university timetable; Adaptive control; Algorithm design and analysis; Computer science; Constraint optimization; Design optimization; Genetic algorithms; Information technology; Programmable control; Simulated annealing; Testing;
Conference_Titel :
Electronics, Circuits and Systems, 2003. ICECS 2003. Proceedings of the 2003 10th IEEE International Conference on
Print_ISBN :
0-7803-8163-7
DOI :
10.1109/ICECS.2003.1301753
