Parallel meta-heuristic approaches to the course timetabling problem

Abstract

The Course Timetabling problem is one of the most difficult combinatorial problems that arises with a University. The main objective of this problem is to obtain a timetable that minimises student conflicts between assigned activities. This is a discrete combinatorial problem that can be extremely difficult to solve for a human expert so computational heuristics are usually implemented in order to find good solutions within a reasonable time. With the advent of multi-core and hyperthreading technologies, parallel heuristics can speed up the solution process and with a proper parallel design these heuristics can improve the quality of solutions with the same number of Fitness evaluations than sequential algorithms. This paper explores the implementation of a parallel set of heuristic algorithms based on genetic algorithms, Scatter Search and discrete PSO for CTTP problem. Our experiments used as benchmark set instances from ITC2007 Track 2. Also the algorithms described in this paper make use of a layer of independence called methodology of design in order to be easily adaptable to new instances. Every parallel algorithm is compared against its sequential counterpart through speed-up metrics like Weak speed-up proposed by Alba et al.