Several Strategies to Improve the Performance of Hyperheuristics for Academic Timetabling Design Problem

The Educational timetabling problem is a common and hard problem inside every educative institution, this problem tries to coordinate Students, Teachers, Classrooms and Timeslots under certain constrains that dependent in many cases the policies of each educational institution. The idea behind hyper-heuristics is to discover some combination of straightforward heuristics to solve a wide range of problems. This paper presents several strategies to improve a GA-based method that produces general hyper heuristics for the educational timetabling design problem using API-Carpio methodology. The GA uses static-length representation, witch involves the complete encoding of a solution algorithm capable to solve schedule design instances. This hyper-heuristic is achieved by learning and testing phases using real instances from Leon Institute of Technology (LIT) producing encouraging results for most of the instances. Finally we analyze the quality of our hyper-heuristic in the context of real Academic Timetabling Design problem against past Investigations.