New nurse scheduling model considering nurses’ seniority and the possibility of consecutive shifts under COVID-19 (A real case study)

References

• M’Hallah R, Alkhabbaz A. Scheduling of nurses: a case study of a Kuwaiti health care unit. Oper Res Health Care. 2013;19(2):1–19.
   Google Scholar
• Jafari H, Bateni S, Daneshvar P, et al. Fuzzy mathematical modeling approach for the nurse scheduling problem: a case study. Int J Fuzzy Syst. 2015;18(2):1–13.
   Web of Science ®Google Scholar
• El Adoly AA, Gheith M, Nashat Fors M. A new formulation and solution for the nurse scheduling problem: a case study in Egypt. Alexandria Eng J. 2018;57(4):2289–2298.
   Web of Science ®Google Scholar
• Tsai CC, Li SHA. A two-stage modeling with genetic algorithms for nurse scheduling problem. Expert Syst Appl. 2009;36(5):9506–9512.
   Web of Science ®Google Scholar
• Osogami T, Imai H. Classification of various neighborhood operations for the nurse scheduling problem. In: International Symposium on Algorithms and Computation. Berlin: Springer; 2000. p. 72–83.
   Google Scholar
• Vanhoucke M, Maenhout B. On the characterization and generation of nurse scheduling problem instances. Eur J Oper Res. 2009;196(2):457–467.
   Web of Science ®Google Scholar
• Şanlıtürk D. Perceived and sources of occupational stress in intensive care nurses during the COVID-19 pandemic. Intensive Crit Care Nurs. 2021;67. doi:10.1016/j.iccn.2021.103107.
   PubMed Web of Science ®Google Scholar
• Cheang B, Li H, Lim A, et al. Nurse rostering problems––a bibliographic survey. Eur J Oper Res. 2003;151:447–460.
   Web of Science ®Google Scholar
• Burke E, De Causmaecker P, Berghe GV, et al. The state of the art of nurse rostering. J Sched. 2004;7:441–499.
   Web of Science ®Google Scholar
• Abdalkareem ZA, Amir A, Al-Betar MA, et al. Healthcare scheduling in optimization context: a review. Health Technol. 2021;11:445–469.
   Web of Science ®Google Scholar
• Sugianto KMS, Hariyati RTS, Muhaeriwati T. An innovation scheduling program of nurses during COVID-19 pandemic: a case study. Int J Nurs Health Serv. 2021;4(2):169–179.
   Google Scholar
• Güler MGM, Geçici E. A decision support system for scheduling the shifts of physicians during COVID-19 pandemic. Comput Ind Eng. 2020;150:106874.
   PubMed Web of Science ®Google Scholar
• El-Rifai O, Garaix T, Xie X. Proactive on-call scheduling during a seasonal epidemic. Oper Res Health Care. 2016;8:53–61.
   Google Scholar
• Liu Y, Wang H, Chen J, et al. Emergency management of nursing human resources and supplies to respond to coronavirus disease 2019 epidemic. Int J Nurs Sci. 2020;7(2):135–138.
   PubMed Web of Science ®Google Scholar
• Zucchi G, Iori M, Subramanian A. Personnel scheduling during COVID-19 pandemic. Optim Lett. 2020;4:1–12.
   Google Scholar
• Lan S, Fan W, Shao K, et al. Medical staff scheduling problem in Chinese mobile cabin hospital during COVID-19 outbreak. In: International Conference on Learning and Intelligent Optimization. Cham (Switzerland): Springer; 2021. p. 211–218.
   Google Scholar
• Abadi MQH, Rahmati S, Sharifi A, et al. HSSAGA: designation and scheduling of nurses for taking care of COVID-19 patients using novel method of hybrid salp swarm algorithm and genetic algorithm. Appl Soft Comput. 2021;108:107449.
   PubMed Web of Science ®Google Scholar
• Valdano E, Poletto C, Boëlle PY, et al. Reorganization of nurse scheduling reduces the risk of healthcare associated infections. Sci Rep. 2021;11(1):7393.
   PubMed Web of Science ®Google Scholar
• Amindoust A, Asadpour M, Shirmohammadi S. A hybrid genetic algorithm for nurse scheduling problem considering the fatigue factor. J Healthc Eng. 2021;2021:Article ID: 5563651. doi:10.1155/2021/5563651.
   PubMed Web of Science ®Google Scholar
• Lishan H, Li T, Lingna Y, et al. The effect of staggered shift scheduling mode on nurses in the COVID-19 isolation ward- a cross sectional study. J Healthc. 2021;58:1–7.
   Google Scholar
• Zhang X, Jiang Z, Yuan X, et al. Nurses reports of actual work hours and preferred work hours per shift among frontline nurses during coronavirus disease 2019 (COVID-19) epidemic: a cross-sectional survey. Int J Nurs Stud Adv. 2021;3:100026.
   PubMedGoogle Scholar
• Caron G, Hansen P, Jaumard B. The assignment problem with seniority and job priority constraints. Oper Res. 1999;47(3):449–453.
   Web of Science ®Google Scholar
• Topaloglu S. A shift scheduling model for employees with different seniority levels and an application in healthcare. Eur J Oper Res. 2009;198(3):943–957.
   Web of Science ®Google Scholar
• Wong TC, Xu M, Chin KS. A two-stage heuristic approach for nurse scheduling problem: a case study in an emergency department. Comput Oper Res. 2014;5:99–110.
   Google Scholar
• Anderson M, Bodur M, Rathwell S, et al. (2021). “Optimization helps scheduling nursing staff at the long-term care homes of the city of Toronto”. Ar Xiv. abs/2102; 09461.
   Google Scholar
• Petrovic S, Vanden Berghe GA. Comparison of two approaches to nurse rostering problems. Ann Oper Res. 2012;194:365–384.
   Web of Science ®Google Scholar
• Breuer DJ, Lahrichi N, Clark DE, et al. Robust combined operating room planning and personnel scheduling under uncertainty. Oper Res Health Care. 2020;27:100276.
   Web of Science ®Google Scholar
• Wickert T, Smet P, Berghe GV. The nurse rerostering problem: strategies for reconstructing disrupted schedules. Comput Oper Res. 2019;104:319–337.
   Web of Science ®Google Scholar
• Tuominen O, Lundgrén-Laine H, Flinkman M, et al. Rescheduling nursing staff with information technology-based staffing solutions: a scoping review. Int J Healthc Technol Manag. 2018;17:145–167.
   Web of Science ®Google Scholar
• Wolbeck L, Kliewer N, Marques I. Fair shift change penalization scheme for nurse rescheduling problems. Eur J Oper Res. 2020;284(3):1121–1135.
   Web of Science ®Google Scholar
• Long Z, Wen X, Lan M, et al. Nursing rescheduling problem with multiple rescheduling methods under uncertainty. Complex Intell Syst. 2021. doi:10.1007/s40747-021-00554-z.
   Web of Science ®Google Scholar
• Nasiri MM, Rahvar M. A two-step multi-objective mathematical model for nurse scheduling problem considering nurse preferences and consecutive shifts. Int J Services Oper Manage. 2017;27(1):83–101.
   Google Scholar
• Burke E, Cowling P, De Causmaecker P, et al. A memetic approach to the nurse rostering problem. Appl Intell. 2001;15:199–214.
   Web of Science ®Google Scholar
• Ingolfsson Md A, Haque A, Umnikov A. Accounting for time-varying queueing effects in workforce scheduling. Eur J Oper Res. 2002;139(3):585–597.
   Web of Science ®Google Scholar
• Yeh JY, Lin WS. Using simulation technique and genetic algorithm to improve the quality care of a hospital emergency department. Expert Syst Appl. 2007;32:1073–1083.
   Web of Science ®Google Scholar
• Aickelin U, Dowsland KA. An indirect genetic algorithm for a nurse-scheduling problem. Comput Oper Res. 2004;31(5):761–778.
   Web of Science ®Google Scholar
• Sadjadi SJ, Soltani R, Izadkhah M, et al. A new nonlinear stochastic staff scheduling model. Scientia Iranica. 2011;18(3):699–710.
   Web of Science ®Google Scholar
• Ala A, Alsaadi FE, Ahmadi M, et al. Optimization of an appointment scheduling problem for healthcare systems based on the quality of fairness service using whale optimization algorithm and NSGA-II. Sci Rep. 2021;11(1):19816.
   PubMed Web of Science ®Google Scholar
• Liu Z, Liu Z, Zhu Z, et al. Simulated annealing for a multi-level nurse rostering problem in hemodialysis service. Appl Soft Comput J. 2017;64. doi:10.1016/j.asoc.2017.12.005.
   Web of Science ®Google Scholar
• Legrain A, Omer J, Rosat S. A rotation-based branch-and-price approach for the nurse scheduling problem. Math Program Comput. 2020;12:417–450.
   Web of Science ®Google Scholar
• Rajeswari M, Amudhavel J, Pothula S, et al. Directed Bee colony optimization algorithm to solve the nurse rostering problem. Comput Intell Neurosci. 2017;20:1–26.
   Google Scholar
• Hamid M, Tavakkoli-Moghaddam R, Golpaygani F, et al. Multi-objective model for a nurse scheduling problem by emphasizing human factors. J Eng Med. 2020;234(2):179–199.
   Google Scholar
• Arajy YZ, Abdullah S, Kifah S. Non-liner great deluge algorithm for handling nurse rostering problem. Int J Appl Eng Res. 2017;12:4959–4966.
   Google Scholar
• Kheiri A, Gretsista A, Keedwell E, et al. A hyper-heuristic approach based upon a hidden Markov model for the multi-stage nurse rostering problem. Comput Oper Res. 2021;130:105221), doi:10.1016/j.cor.2021.105221.
   Web of Science ®Google Scholar
• Jaradat GM, Al-Badareen A, Ayob M, et al. Hybrid elitist-ant system for nurse-rostering problem. J King Saud University – Comput Inf Sci. 2019;31(3):378–384. doi:10.1016/j.jksuci.2018.02.009.
   Web of Science ®Google Scholar
• Rahimian E, Akartunal K, Levine J. A hybrid integer and constraint programming approach to solve nurse rostering problems. Comput Oper Res. 2017;82:83–94.
   Web of Science ®Google Scholar
• Awadallah MA, Al-Betar MA, Khader AT, et al. Hybridization of harmony search with hill climbing for highly constrained nurse rostering problem. Neural Comput Appl. 2017;28:463–482.
   Web of Science ®Google Scholar
• Ramli R, Abdul Rahman R, Rohim N. A hybrid ant colony optimization algorithm for solving a highly constrained nurse rostering problem. J Inf Commun Technol. 2019;18(3):305–326.
   Google Scholar
• Chen PS, Zeng ZY. Developing two heuristic algorithms with meta-heuristic algorithms to improve solutions of optimization problems with soft and hard constraints: an application to nurse rostering problems. Appl Soft Compu J. 2020;93:106336.
   Web of Science ®Google Scholar
• Turhan AM, Bilgen B. A hybrid fix-and-optimize and simulated annealing approaches for nurse rostering problem. Comput Ind Eng. 2020;145:106531.
   Web of Science ®Google Scholar
• Davoudi A, Ahmadi M, Sharifi A, et al. Studying the effect of taking statins before infection in the severity reduction of COVID-19 with machine learning. Biomed Res Int. 2021;19(2021):9995073.
   Google Scholar
• Sharifi A, Ahmadi M, Mehni MA, et al. Experimental and numerical diagnosis of fatigue foot using convolutional neural network. Comput Methods Biomech Biomed Engin. 2021;24(16):1828–1840.
   PubMed Web of Science ®Google Scholar
• Farid M, Purdy N, Neumann WP. Using system dynamics modelling to show the effect of nurse workload on nurses’ health and quality of care. Ergonomics. 2020;63(8):952–964.
   PubMed Web of Science ®Google Scholar
• Nyarko EK, Scitovski R. Solving the parameter identification problem of mathematical models using genetic algorithms. Appl Math Comput. 2004;153:651–658.
   Web of Science ®Google Scholar
• Wibowo A, Lianawati Y. A multi-objective genetic algorithm for optimizing the nurse scheduling problem. Int J Recent Technol Eng. 2019;8(3):5409–5414.
   Google Scholar