BOA for nurse scheduling


Autoria(s): Li, Jingpeng; Aickelin, Uwe
Contribuinte(s)

Pelikan, Martin

Sastry, Kumara

Cantú-Paz, Erick

Data(s)

2006

Resumo

Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimization Algorithm (BOA)for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each nurse’s assignment. Based on the idea of using probabilistic models, the BOA builds a Bayesian network for the set of promising solutions and samples these networks to generate new candidate solutions. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed algorithm may be suitable for other scheduling problems.

Formato

application/pdf

Identificador

http://eprints.nottingham.ac.uk/1248/1/li2006.pdf

Li, Jingpeng and Aickelin, Uwe (2006) BOA for nurse scheduling. In: Scalable optimization via probabilistic modeling: from algorithms to applications. Studies in computational intelligence, 33 (33). Springer. ISBN 9783540349532

Idioma(s)

en

Publicador

Springer

Relação

http://eprints.nottingham.ac.uk/1248/

Tipo

Book Section

PeerReviewed