Integer programming model extensions for a multi-stage nurse rostering problem

Mischek, Florian; Musliu, Nysret

doi:10.1007/s10479-017-2623-z

Cited by 19 publications

(17 citation statements)

References 15 publications

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“…They showed that their scheduling not only improves the satisfaction level of nurses but also decreases their overtime up to 36%. Mischek and Musliu 17 developed and assessed several extensions of standard integer programming formulations for nurse rostering problems to cope with multi-stage settings. The soft constraints considered in their study include insufficient staffing for optimal coverage, the number of consecutive shifts and days off, the number of possible working weekends, and so on.…”

Section: Literature Reviewmentioning

confidence: 99%

A multi-objective model for a nurse scheduling problem by emphasizing human factors

Hamid

Tavakkoli–Moghaddam

Golpaygani

et al. 2019

Proc Inst Mech Eng H

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Assigning nurses to appropriate departments and work shifts based on human factors can strengthen teamwork and boost the efficiency of healthcare systems. The human factors considered in this study include skill, preference, and compatibility of nurses. In this regard, a unique multi-objective mathematical model for nurse scheduling is proposed in this article, in which nurses’ decision-making styles are taken into account. Three objectives, including minimization of the total cost of staffing, minimization of the sum of incompatibility among nurses’ decision-making styles assigned to the same shift days, and maximization of the overall satisfaction of nurses for their assigned shifts, are addressed in this model. Three meta-heuristics, namely, multi-objective Keshtel algorithm, non-dominated sorting genetic algorithm II, and multi-objective tabu search, are developed to solve the problem. Moreover, a data envelopment analysis method is employed to rank the obtained Pareto solutions. Afterwards, a real-life case at a large hospital in Tehran, Iran, is investigated. Eventually, the applicability and effectiveness of the proposed model are assessed based on the experimental results.

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Section: Literature Reviewmentioning

confidence: 99%

A multi-objective model for a nurse scheduling problem by emphasizing human factors

Hamid

Tavakkoli–Moghaddam

Golpaygani

et al. 2019

Proc Inst Mech Eng H

View full text Add to dashboard Cite

show abstract

“…The first solver was based on the exact method using the MILP solver CPLEX (v. 12.5), Meanwhile the second solver was implemented using EasyLocal++ (v.3). In addition [50] had also solved the dynamic version for NRP. The researchers have added a new expansion to the problem in the version of additional constraints to address incomplete data, and have used an integer programming model to solve the problem.…”

Section: Nrp-based Optimization Methodsmentioning

confidence: 99%

“…All soft constraints have been correlated with weights, based on its importance to the patients. The highest weight is associated with SC3, transfer patients are adding (100) to the objective function, the second-highest weight is for SC1, which is related to the gender policy for the patients, it is weighted (50) adding to the cost. The rest are Department specialism, Room feature is weighted (20), while Room Preference is (20).…”

Section: Patient Admission Scheduling Problem Under Uncertainty (Pasu) Versionmentioning

confidence: 99%

Healthcare scheduling in optimization context: a review

et al. 2021

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This paper offers a summary of the latest studies on healthcare scheduling problems including patients’ admission scheduling problem, nurse scheduling problem, operation room scheduling problem, surgery scheduling problem and other healthcare scheduling problems. The paper provides a comprehensive survey on healthcare scheduling focuses on the recent literature. The development of healthcare scheduling research plays a critical role in optimizing costs and improving the patient flow, providing prompt administration of treatment, and the optimal use of the resources provided and accessible in the hospitals. In the last decades, the healthcare scheduling methods that aim to automate the search for optimal resource management in hospitals by using metaheuristics methods have proliferated. However, the reported results are disintegrated since they solved every specific problem independently, given that there are many versions of problem definition and various data sets available for each of these problems. Therefore, this paper integrates the existing results by performing a comprehensive review and analyzing 190 articles based on four essential components in solving optimization problems: problem definition, formulations, data sets, and methods. This paper summarizes the latest healthcare scheduling problems focusing on patients’ admission scheduling problems, nurse scheduling problems, and operation room scheduling problems considering these are the most common issues found in the literature. Furthermore, this review aims to help researchers to highlight some development from the most recent papers and grasp the new trends for future directions.

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“…In [30] another IP model was developed to generate optimal nurses' schedules for an emergency center of a Specialist Hospital. An extended model of standard IP formulation for NRP was proposed in [26] to solve the multistage NRP of the Second International Nurse Rostering Competition [14], where competitive results were reported.…”

mentioning

confidence: 99%

A hybrid variable neighbourhood search and dynamic programming approach for the nurse rostering problem

Abdelghany¹,

Eltawil²,

Yahia³

et al. 2021

JIMO

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Nurse Rostering is the activity of assigning nurses to daily shifts in order to satisfy the cover requirements, taking into account the operational requirements and nurses' preferences. The problem is usually modeled as sets of hard and soft constraints with an objective function to minimize violations of soft constraints. The nurse rostering problem is known to be NP-hard. Many metaheuristics were used to tackle this problem. One of the frequently used heuristics is the Variable Neighbourhood Search (VNS). The VNS is usually used as a standalone method or in integration with another exact or heuristic method. In this paper, a new hybrid VNS and Dynamic Programming based heuristic approach is proposed to handle the nurse rostering problem. In the proposed approach, two perturbation mechanisms are adopted simultaneously. The proposed approach is tested on two different benchmark data sets. A comparison with state-of-the-art methods from literature revealed the competitive performance of the proposed approach.2010 Mathematics Subject Classification. Primary: 90B35; Secondary: 90C59, 90C39.

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Integer programming model extensions for a multi-stage nurse rostering problem

Cited by 19 publications

References 15 publications

A multi-objective model for a nurse scheduling problem by emphasizing human factors

A multi-objective model for a nurse scheduling problem by emphasizing human factors

Healthcare scheduling in optimization context: a review

A hybrid variable neighbourhood search and dynamic programming approach for the nurse rostering problem

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