A guided search non-dominated sorting genetic algorithm for the multi-objective university course timetabling problem.

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dc.contributor.author Jat, Sadaf Naseem en
dc.contributor.author Yang, Shengxiang en
dc.date.accessioned 2013-05-24T09:42:16Z
dc.date.available 2013-05-24T09:42:16Z
dc.date.issued 2011
dc.identifier.citation Jat, S. and Yang, S. (2011) A guided search non-dominated sorting genetic algorithm for the multi-objective university course timetabling problem. In: Evolutionary Computation in Combinatorial Optimization: Proceedings of 11th European Conference, EvoCOP 2011, Torino, April 2011. Berlin: Springer-Verlag, pp. 1-13. en
dc.identifier.isbn 978-3-642-20363-3
dc.identifier.uri http://hdl.handle.net/2086/8669
dc.description.abstract The university course timetabling problem is a typical combinatorial optimization problem. This paper tackles the multi-objective university course timetabling problem (MOUCTP) and proposes a guided search non-dominated sorting genetic algorithm to solve the MOUCTP. The proposed algorithm integrates a guided search technique, which uses a memory to store useful information extracted from previous good solutions to guide the generation of new solutions, and two local search schemes to enhance its performance for the MOUCTP. The experimental results based on a set of test problems show that the proposed algorithm is efficient for solving the MOUCTP. en
dc.language.iso en en
dc.publisher Springer-Verlag. en
dc.relation.ispartofseries Lecture Notes on Computer Science;Vol. 6622
dc.title A guided search non-dominated sorting genetic algorithm for the multi-objective university course timetabling problem. en
dc.type Article en
dc.identifier.doi http://dx.doi.org/10.1007/978-3-642-20364-0_1
dc.researchgroup Centre for Computational Intelligence en
dc.peerreviewed Yes en


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