Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/5818
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yang, S | - |
dc.contributor.author | Jat, SN | - |
dc.date.accessioned | 2011-09-19T13:07:02Z | - |
dc.date.available | 2011-09-19T13:07:02Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(1): 93 - 106, Jan 2011 | en_US |
dc.identifier.issn | 1094-6977 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/5818 | - |
dc.description | This article is posted here with permission from the IEEE - Copyright @ 2011 IEEE | en_US |
dc.description.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. | en_US |
dc.description.sponsorship | This work was supported by the Engineering and Physical Sciences Research Council of U.K. under Grant EP/E060722/1. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | Genetic algorithm (GA) | en_US |
dc.subject | Guided search | en_US |
dc.subject | Local search (LS) | en_US |
dc.subject | University course timetabling problem (UCTP) | en_US |
dc.title | Genetic algorithms with guided and local search strategies for university course timetabling | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1109/TSMCC.2010.2049200 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel (Active) | - |
pubs.organisational-data | /Brunel/Brunel (Active)/School of Info. Systems, Comp & Maths | - |
pubs.organisational-data | /Brunel/Research Centres (RG) | - |
pubs.organisational-data | /Brunel/Research Centres (RG)/CIKM | - |
pubs.organisational-data | /Brunel/School of Information Systems, Computing and Mathematics (RG) | - |
pubs.organisational-data | /Brunel/School of Information Systems, Computing and Mathematics (RG)/CIKM | - |
Appears in Collections: | Publications Computer Science Dept of Computer Science Research Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Fulltext.pdf | 609.46 kB | Adobe PDF | View/Open |
Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.