Publications in Scientific Journals:

C. Nothegger, A. Mayer, A Chwatal, G. Raidl:
"Solving the post enrolment course timetabling problem by ant colony optimization";
Annals of Operations Research, Volume 194 (2012), 1; 325 - 339.

English abstract:
In this work we present a new approach to tackle the problem of Post Enrolment
Course Timetabling as specified for the International Timetabling Competition 2007
(ITC2007), competition track 2. The heuristic procedure is based on Ant Colony Optimization
(ACO) where artificial ants successively construct solutions based on pheromones (stigmergy)
and local information. The key feature of our algorithm is the use of two distinct but
simplified pheromone matrices in order to improve convergence but still provide enough
flexibility for effectively guiding the solution construction process. We show that by parallelizing
the algorithm we can improve the solution quality significantly. We applied our
algorithm to the instances used for the ITC2007. The results document that our approach
is among the leading algorithms for this problem; in all cases the optimal solution could
be found. Furthermore we discuss the characteristics of the instances where the algorithm
performs especially well.

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.