A comparison of genetic algorithms & tabu search for a course timetabling problem

Abstract

Finding a solution to the course timetabling problem is a highly difficult optimization problem due to the wide variety of constraints and the potentially huge size of the data to handle. Genetic algorithms and tabu search are two solution methods which are widely used for timetabling problems. In this study, these two methods have been applied to the course timetabling problem defined. Two separate computer programs have been developed to employ each of the solution methods, and these two programs have been run with the same input data. The two methods have then been compared with respect to the quality of the best solution reported by each program, the route in the solution space leading to the best solution reported, and the cost of finding each of the best solution. The best solutions have been observed not to be significantly different in quality.