Bayesian Optimisation Algorithm for Nurse Scheduling
Neural and Evolutionary Computing
2010-07-05 v1 Computational Engineering, Finance, and Science
Abstract
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 nurses 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.
Cite
@article{arxiv.0804.0524,
title = {Bayesian Optimisation Algorithm for Nurse Scheduling},
author = {Jingpeng Li and Uwe Aickelin},
journal= {arXiv preprint arXiv:0804.0524},
year = {2010}
}