Solving a real-world nurse rostering problem by Simulated Annealing

被引：7

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

来源：

OPERATIONS RESEARCH FOR HEALTH CARE | 2023年 / 36卷

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

页数：11

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