A two-stage heuristic algorithm for the nurse scheduling problem with fairness objective on weekend workload under different shift designs

Zhong, Xiang; Zhang, Jingyu; Zhang, Xuanqi

doi:10.1080/24725579.2017.1356891

Cited by 15 publications

(11 citation statements)

References 33 publications

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“…Here, the objective function (16) minimizes the number of days worked by full-time nurses given that the total number of hours worked by all nurses is as small as possible. Constraint (17) indicates that a sufficient number of nurses must work daily to meet the patients' needs. Constraint (18) indicates that there should not be a considerable difference between the work periods of different full-time nurses in the scheduling cycle to ensure fairness.…”

Section: Methodsmentioning

confidence: 99%

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Applying Queuing Theory and Mixed Integer Programming to Blood Center Nursing Schedules of a Large Hospital in China

Luo

Liu

Cui

et al. 2020

Computational and Mathematical Methods in Medicine

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Blood centers in large hospitals in China are facing serious problems, including complex patient queues and inflexible nursing schedules. This study is aimed at developing a flexible scheduling method for blood center nurses. By systematically analyzing the constraints that affect scheduling, a flexible scheduling model is established based on queuing theory and mixed integer programming. This combined model can reasonably determine the number of nurses required during a given working period and flexibly arrange nursing schedules while ensuring sufficient rest periods for individual nurses. Results of numerical studies conducted using data from a large hospital in China show a significant improvement in patient waiting time performance metrics over the hospital’s current practice. In addition, the nurses’ workloads and rest periods are well balanced, indicating that the proposed method can effectively and flexibly arrange nursing shifts in blood centers.

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Section: Methodsmentioning

confidence: 99%

“…Lin designed an adaptive scheduling heuristic algorithm that reduces the patients' waiting times [16]. Zhong et al proposed a two-stage heuristic algorithm for nurse scheduling to achieve fairness and flexibility goals [17].…”

Section: Introductionmentioning

confidence: 99%

Applying Queuing Theory and Mixed Integer Programming to Blood Center Nursing Schedules of a Large Hospital in China

Luo

Liu

Cui

et al. 2020

Computational and Mathematical Methods in Medicine

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show abstract

“…As for the objective to purse in defining the staff roster, the literature acknowledges that ensuring shift equity is crucial, as equity drives staff satisfaction and consequently service quality (Dewa et al 2017). This is particularly true for burnout exposed personnel such as physicians (Adams et al 2019;Stolletz and Brunner 2012;Zhong et al 2017). Balancing personnel workload is one of the most commonly used approaches to guarantee equity (Cappanera and Scutellà 2011;Cappanera et al 2014).…”

Section: Literature Overviewmentioning

confidence: 99%

“…As an example, day-offs are assigned in the first phase, and then the resulting solution is used as the input of the second phase in which working shifts are assigned (e.g. Valouxis et al 2012;Zhong et al 2017). It is worth to point out, however, that in these studies the two-phase approach is considered as a mean to reduce the computational complexity of problems that would not otherwise be possible to solve in one shot, rather than, as in our study, as a tool to optimally address problems at a different level of decision-making and to manage balancing criteria with different scopes.…”

Section: Literature Overviewmentioning

confidence: 99%

The emergency department physician rostering problem: obtaining equitable solutions via network optimization

2021

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In this study, we address workload balancing in Emergency Department Physician Rostering Problems. We propose a two-phase approach to deal with two common workload balancing issues: (1) the even distribution of worked weekends and weekend night shifts across physicians in the long term, and (2) the even distribution of morning and afternoon shifts in the medium term. To implement such an approach, we have developed two Integer Linear Programming (ILP) models, one for each phase. In the first phase, we determine the weekends that each physician will be on duty over the long term planning horizon (6-months) while evenly distributing the workload (worked weekends and weekend night shifts) across physicians. In the second phase, month by month, we iteratively determine the workday shifts of each physician while pursuing the even distribution of workload (morning and afternoon shifts) across physicians. The second phase relies on the solution of the first phase, i.e., the weekend shifts assigned to each physician in the first phase are considered preassigned shifts in the second phase. In both phases, we consider the constraints deriving from collective as well as individual contractual agreements (e.g. constraints limiting the maximum number of night shifts each physician can work every month, their maximum weekly and monthly workload, etc.) as well as individual physician’s preferences and desiderata. The problems addressed in the two phases differ in terms of the planning horizon, objective function, and constraints, yet they are both modeled as multicommodity ow problems and share the same network structure. Also, we define some families of simple yet effective, valid inequalities that are crucial to address the computational complexity of the first-phase problem. The proposed optimization models have been tested on real data from a leading European Hospital and on benchmark instances from the literature. The models’ effectiveness has been assessed through six key performance indicators purposely defined. Results demonstrate that the presented models allow considering the complex nature of physicians rostering problems and obtaining well-balanced and thus equitable work schedules.

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“…An iterated local search is proposed as the solving tool. Zhong et al [38] develop a two-stage heuristic algorithm to create a nurse schedule with a balanced weekend workload. e algorithm accounts for the individual nurse preferences, patient volume fluctuation, required patient-to-nurse ratio, and other work-rest rules.…”

mentioning

confidence: 99%

A Goal Programming Approach to Nurse Scheduling with Individual Preference Satisfaction

Rerkjirattikal

Huynh

Olapiriyakul

et al. 2020

Mathematical Problems in Engineering

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The use of scheduling optimization tools is essential in creating an efficient nurse shift-rotation schedule. A well-designed nurse scheduling technique can improve nurses’ job satisfaction and their intention to stay. This study develops a goal programming approach to nurse scheduling that simultaneously considers workload fairness and individual preferences on working shift and day off assignments. A case study of an operating room at a hospital in Thailand is used to illustrate the model capabilities for solving an actual nurse scheduling problem. The job satisfaction factors defined based on an interview and questionnaire survey are integrated into the model. When compared against the manual scheduling result, the optimal schedules can be implemented to improve the nurse’s perception of fairness and preference satisfaction. The analysis of fairness and multiple individual preferences based on a case study investigation is the main contribution of this study.

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A two-stage heuristic algorithm for the nurse scheduling problem with fairness objective on weekend workload under different shift designs

Cited by 15 publications

References 33 publications

Applying Queuing Theory and Mixed Integer Programming to Blood Center Nursing Schedules of a Large Hospital in China

Applying Queuing Theory and Mixed Integer Programming to Blood Center Nursing Schedules of a Large Hospital in China

The emergency department physician rostering problem: obtaining equitable solutions via network optimization

A Goal Programming Approach to Nurse Scheduling with Individual Preference Satisfaction

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