Adaptive local search approach for the timetable scheduling problem

In this paper, we present a new Adaptive Local Search approach (ALS) and its implementation for the NP hard Timetable Scheduling Problem. This approach uses graph heuristics to generate the initial solution and the Aspiration criterion with Random moves strategies to improve a guided local search procedure for the search process. Experimental results on a collection of data sets from the popular Carter's benchmark demonstrated very promising results when compared with several existing state of the art approaches.