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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(3): 255-258 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.314

Timetabling: A State-of-the-Art Evolutionary Approach

M. Doulaty, M. R. Feizi Derakhshi, and M. Abdi
Abstract—Timetabling is the task of creating a schedule while satisfying some constraints. This problem is an NPComplete problem, so solving it needs some heuristics. There are many types of timetabling; we mainly focused on university course timetabling. There have been many efforts in literature, but most of them have used some limiting assumptions that cause their approach to be unusable in real situations. We've used an evolutionary approach based on genetic algorithm to solve this problem in real situation and in a reasonable amount of time. We've used real data from our department in the university and our approach could solve the problem in about 15 minutes, while manually timetabling may take three days.

Index Terms—Timetabling, university timetabling, genetic algorithm.

Mortaza Doulaty is with the Department of Computer Science, University of Sheffield, Sheffield, UK (e-mail: m.doulaty@dcs.shef.ac.uk). Mohammad-Reza Feizi-Derakhshi is with the Department of Computer Science, University of Tabriz, Tabriz, Iran (e-mail: mfeizi@tabrizu.ac.ir). Mehrdad Abdi is with the Amirkabir University of Tehran, Tehran, Iran (e-mail: m.abdi@aut.ac.ir).

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Cite:M. Doulaty, M. R. Feizi Derakhshi, and M. Abdi, "Timetabling: A State-of-the-Art Evolutionary Approach," International Journal of Machine Learning and Computing vol.3, no. 3, pp. 255-258, 2013.

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