Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/5880
Title: | A guided search genetic algorithm for the university course timetabling problem |
Authors: | Jat, SN Yang, S |
Issue Date: | 2009 |
Publisher: | MISTA 2009 |
Citation: | The 4th Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA 2009), Dublin, Ireland: 180 - 191, 10 - 12 Aug 2009 |
Abstract: | The university course timetabling problem is a combinatorial optimisation problem in which a set of events has to be scheduled in time slots and located in suitable rooms. The design of course timetables for academic institutions is a very difficult task because it is an NP-hard problem. This paper proposes a genetic algorithm with a guided search strategy and a local search technique for the university course timetabling problem. The guided search strategy is used to create offspring into the population based on a data structure that stores information extracted from previous good individuals. The local search technique is used to improve the quality of individuals. The proposed genetic algorithm is tested on a set of benchmark problems in comparison with a set of state-of-the-art methods from the literature. The experimental results show that the proposed genetic algorithm is able to produce promising results for the university course timetabling problem. |
Description: | Copyright @ 2009 MISTA |
URI: | http://bura.brunel.ac.uk/handle/2438/5880 |
Appears in Collections: | Publications Computer Science Dept of Computer Science Research Papers |
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