Dynamic programming with approximation function for nurse scheduling

Shi, Peng and Landa-Silva, Dario (2016) Dynamic programming with approximation function for nurse scheduling. Lecture Notes in Computer Science, 10122 . pp. 269-280. ISSN 0302-9743

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Although dynamic programming could ideally solve any combinatorial optimization problem, the curse of dimensionality of the search space seriously limits its application to large optimization problems. For example, only few papers in the literature have reported the application of dynamic programming to workforce scheduling problems. This paper investigates approximate dynamic programming to tackle nurse scheduling problems of size that dynamic programming cannot tackle in practice. Nurse scheduling is one of the problems within workforce scheduling that has been tackled with a considerable number of algorithms particularly meta-heuristics. Experimental results indicate that approximate dynamic programming is a suitable method to solve this problem effectively.

Item Type: Article
Additional Information: The final publication is available at link.springer.com. 2nd International Workshop on Machine Learning, Optimization and Big Data (MOD 2016), Volterra, Italy, 26-29 August 2016.
Keywords: Markov Decision Process, Approximate Dynamic Programming, Nurse Scheduling Problem
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1007/978-3-319-51469-7_23
Depositing User: Landa-Silva, Dario
Date Deposited: 24 Mar 2017 11:59
Last Modified: 08 May 2020 11:45
URI: https://eprints.nottingham.ac.uk/id/eprint/35585

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