Solving a real-world nurse rostering problem by Simulated Annealing

被引:8
作者
Ceschia, Sara [1 ]
Di Gaspero, Luca [1 ]
Mazzaracchio, Vincenzo [2 ]
Policante, Giuseppe [2 ]
Schaerf, Andrea [1 ]
机构
[1] Univ Udine, DPIA, Via Sci 206, I-33100 Udine, Italy
[2] WINDEX srl, Via S Chiara 22, I-37012 Bussolengo, Italy
关键词
Nurse rostering; Real-world application; Local search; Simulated Annealing; Practice of OR; OPTIMIZATION; STRATEGIES;
D O I
10.1016/j.orhc.2023.100379
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Designing high quality nurse rostering plans is essential for health care facilities in order to guarantee efficiency, safety and quality-of-care balanced with staff well-being. We introduce a new real-world formulation for the nurse rostering problem, arising in many Italian healthcare institutions, which has been developed in collaboration with a primary software company in the field. It considers nurses with different skills, special shifts depending on the skills, time work-load limits, and different types of days-off. In addition, preferences and incompatibilities between nurses are taken into account. We propose a MIP model and a local search method, driven by a Simulated Annealing metaheuristic, based on a combination of two neighborhoods. The solution method was tested on 34 real-world instances coming from various healthcare institutions in North Italy. The dataset is available at https://bitbucket.org/satt/nrp-instances, along with our best solutions. (c) 2023 Elsevier Ltd. All rights reserved.
引用
收藏
页数:11
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