Exact/heuristic hybrids using rVNS and hyperheuristics for workforce scheduling
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2007Keyword
Workforce schedulingReduced Variable Neighbourhood Search (rVNS)
Hyperheuristic
Genetic algorithms
Optimimisation
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© 2008 Springer-Verlag. Reproduced in accordance with the publisher's self-archiving policy. Original publication is available at http://www.springerlink.comPeer-Reviewed
Yes
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In this paper we study a complex real-world workforce scheduling problem. We propose a method of splitting the problem into smaller parts and solving each part using exhaustive search. These smaller parts comprise a combination of choosing a method to select a task to be scheduled and a method to allocate resources, including time, to the selected task. We use reduced Variable Neighbourhood Search (rVNS) and hyperheuristic approaches to decide which sub problems to tackle. The resulting methods are compared to local search and Genetic Algorithm approaches. Parallelisation is used to perform nearly one CPU-year of experiments. The results show that the new methods can produce results fitter than the Genetic Algorithm in less time and that they are far superior to any of their component techniques. The method used to split up the problem is generalisable and could be applied to a wide range of optimisation problems.Version
Accepted manuscriptCitation
Remde SM, Cowling PI, Dahal KP et al (2007) Exact/heuristic hybrids using rVNS and hyperheuristics for workforce scheduling. In: Evolutionary computation in combinatorial optimization. Proceedings of the 7th European Conference (EvoCOP 2007) Valencia, Spain, April 11-13, 2007: 188-197.Link to Version of Record
https://doi.org/10.1007/978-3-540-71615-0_17Type
Conference paperae974a485f413a2113503eed53cd6c53
https://doi.org/10.1007/978-3-540-71615-0_17