Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5818
Title: Genetic algorithms with guided and local search strategies for university course timetabling
Authors: Yang, S
Jat, SN
Keywords: Genetic algorithm (GA);Guided search;Local search (LS);University course timetabling problem (UCTP)
Issue Date: 2011
Publisher: IEEE
Citation: IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(1): 93 - 106, Jan 2011
Abstract: The university course timetabling problem (UCTP) is a combinatorial optimization problem, in which a set of events has to be scheduled into time slots and located into suitable rooms. The design of course timetables for academic institutions is a very difficult task because it is an NP-hard problem. This paper investigates genetic algorithms (GAs) with a guided search strategy and local search (LS) techniques for the UCTP. The guided search strategy is used to create offspring into the population based on a data structure that stores information extracted from good individuals of previous generations. The LS techniques use their exploitive search ability to improve the search efficiency of the proposed GAs and the quality of individuals. The proposed GAs are tested on two sets of benchmark problems in comparison with a set of state-of-the-art methods from the literature. The experimental results show that the proposed GAs are able to produce promising results for the UCTP.
Description: This article is posted here with permission from the IEEE - Copyright @ 2011 IEEE
URI: http://bura.brunel.ac.uk/handle/2438/5818
DOI: http://dx.doi.org/10.1109/TSMCC.2010.2049200
ISSN: 1094-6977
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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