@inproceedings{622c0a18f7164c979b0ec6d16dbaa40d,
title = "A timetabling applied case solved with ant colony optimization",
abstract = "This research present an applied case of the resolution of a timetabling problem called the University course Timetabling problem (UCTP), the resolution technique used is based in Ant Colony Optimization metaheuristic. Ant Colony Optimization is a Swarm Intelligence technique which inspired from the foraging behavior of real ant colonies. We propose a framework to solve the University course Timetabling problem effectively. We show the problem and the resolution design using this framework. First we tested our proposal with some competition instances, and then compare our results with other techniques. The results show that our proposal is feasible and competitive with other techniques. To evaluate this framework in practice way, we build a real instance using the case of the school of Computer Science Engineering of the Pontifical Catholic University of Valpara{\'i}so and the Department of Computer Engineering at Playa Ancha University.",
keywords = "Ant Colony Optimization, Swarm Intelligence, University Course Timetabling Problem",
author = "Broderick Crawford and Ricardo Soto and Franklin Johnson and Fernando Paredes",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 4th Computer Science On-line Conference, CSOC 2015 ; Conference date: 27-04-2015 Through 30-04-2015",
year = "2015",
doi = "10.1007/978-3-319-18476-0_27",
language = "English",
isbn = "9783319184753",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "267--276",
editor = "Radek Silhavy and Roman Senkerik and Oplatkova, {Zuzana Kominkova} and Zdenka Prokopova and Petr Silhavy",
booktitle = "Artificial Intelligence Perspectives and Applications - Proceedings of the 4th Computer Science On-line Conference 2015, CSOC 2015",
}