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optimization-algorithms ======================= Combinatorial optimization algorithms written in Python 3.4 for solving timetabling problem scenarios. In this work algorithms for solving NP-Complete combinatorial problems of timetabling were made based on literature, which describes the relevant methods created until now for solving these kind of problems. The intention of this project was to compare the main algorithms described in the literature on solving timetabling problems. The scenarios provided for the algorithms are generated by another algorithm, also created in this work. By knowledge limitations of the author the structured programming paradigm was used to make all the algorithms, because of that the scenario generation algorithm demanded a lot of more time than expected to code it, this is also because of the complexity of variables that this algorithm is capable of generating in order to be as close as possible to reality. Provided that, not all studied algorithms were created, in fact just 2 algorithms came to be realeased, which comprimised the main goal of this project: comparing the computational efficiency of the main algorithms described in literature. Although the work on the development of the scenario generation algorithm was successful. This work is product of the undergraduation research program PDPD (in portuguese, Pesquisando Desde o Primeiro Dia) performed by Rodrigo Martins de Oliveira, with guidance of Jess Pascual Mena-Chalco, at Universidade Federal do ABC, which the author thanks for the financial assitance over the period from November 2013 to July 2014.

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