Sara Ceschia , Luca Di Gaspero , Vincenzo Mazzaracchio , Giuseppe Policante , Andrea Schaerf
{"title":"用模拟退火法解决现实世界的护士名册问题","authors":"Sara Ceschia , Luca Di Gaspero , Vincenzo Mazzaracchio , Giuseppe Policante , Andrea Schaerf","doi":"10.1016/j.orhc.2023.100379","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p><p>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.</p><p>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 <span>https://bitbucket.org/satt/nrp-instances</span><svg><path></path></svg>, along with our best solutions.</p></div>","PeriodicalId":46320,"journal":{"name":"Operations Research for Health Care","volume":"36 ","pages":"Article 100379"},"PeriodicalIF":1.5000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Solving a real-world nurse rostering problem by Simulated Annealing\",\"authors\":\"Sara Ceschia , Luca Di Gaspero , Vincenzo Mazzaracchio , Giuseppe Policante , Andrea Schaerf\",\"doi\":\"10.1016/j.orhc.2023.100379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p><p>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.</p><p>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 <span>https://bitbucket.org/satt/nrp-instances</span><svg><path></path></svg>, along with our best solutions.</p></div>\",\"PeriodicalId\":46320,\"journal\":{\"name\":\"Operations Research for Health Care\",\"volume\":\"36 \",\"pages\":\"Article 100379\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Research for Health Care\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2211692323000024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research for Health Care","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211692323000024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Solving a real-world nurse rostering problem by Simulated Annealing
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.
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