Nurse Scheduling Problem: An Integer Programming Model with a Practical Application

Fan, Neng; Syed, Mujahid N.; Zhang, Jicong; Georgiev, Pando; Papajorgji, Petraq; Steponavičė, Ingrida; Neugaard, Britta; Pardalos, Pãnos M.

doi:10.1007/978-1-4614-5094-8_5

Cited by 9 publications

(8 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The SAA algorithm is also used for handling the associations among the weeks without rising the computational time. In the dynamic 35 constraints are like single assignment per day, under-staffing, shift type successions and soft constraints are like consecutive assignments, consecutive resting days, and complete week-end. A multi-objective function is generated based on these constraints, and the dynamic scheduling of nurses is done in such a way that the concerned objective function should attain minimum value.…”

Section: Proposed Architecturementioning

confidence: 99%

See 1 more Smart Citation

Sea lion attacking‐based deer hunting optimization algorithm for dynamic nurse scheduling in health care sector contribution of hybrid algorithm in cloud

Sarkar¹,

Aryan²,

Chaki

2022

Concurrency and Computation

View full text Add to dashboard Cite

Summary The main intent of this article is to frame the dynamic NSP in the cloud using a multi‐objective optimization strategy. The benefit of the dynamic scheduling over static scheduling is that the scheduling will be done week by week based on the available number of nurses. For solving this problem, several constraints like single assignment per day, under‐staffing, shift type successions, consecutive assignments, consecutive resting days, and complete week‐end are considered. With reference to these constraints, a minimized objective function is used based on the nurse demand in week by week. Each constraint is having some conditions for solving this problem. These schedules are stored in cloud for efficient decision making regarding NSP and it helps in assisting the future scheduling purposes. It also offers secure storage when compared to the other storage devices. As a novelty, this article tries to employ the hybrid meta‐heuristic algorithm called sea lion attacking‐based deer hunting optimization algorithm. Hybrid optimization algorithms have been reported to be promising for certain search problems with a higher convergence rate. Hence, the developed hybrid optimization algorithm hardly helps to generate a feasible and near‐optimal schedule at the end of the horizon.

show abstract

Section: Proposed Architecturementioning

confidence: 99%

“…The position angle's update process is denoted as Equation ( 34) that is measured based on the difference between the visual angle and the wind angle. In order to update the position angle for the successive iteration and the corresponding equation is indicated in Equation (35).…”

Section: Conventional Dhoamentioning

confidence: 99%

Sea lion attacking‐based deer hunting optimization algorithm for dynamic nurse scheduling in health care sector contribution of hybrid algorithm in cloud

Sarkar¹,

Aryan²,

Chaki

2022

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…Constraint minimization [21] is a primary issue in all nurse scheduling problems. In this regard, popular Branch and Price methods and Integer programming are used in [22][23][24], respectively, to minimize the constraints and to reduce cost. Another paper [25] uses Constraint Programming (CP) to solve the scheduling problems in a French hospital.…”

Section: Mathematical Programmingmentioning

confidence: 99%

A Patient-Centric Nurse Scheduling Algorithm

2021

View full text Add to dashboard Cite

This paper introduces a new approach to the well-studied nurse scheduling problem. Nurse scheduling problem involves multiple inter-related parameters concerning nurse and patients, which makes the problem too complex. As a result, many of the traditional NSPs are forced to consider only the nurse-respective parameters for generating the schedules. In this paper, we have considered patient recovery as the ultimate objective of nurse scheduling. To achieve this, we have considered patient's needs and priorities besides the nurse skills, and environment (e.g. logistic) parameters as basic constraints. This paper aims to minimize soft constraints as well as to improve patient's satisfaction and quality of service of nurse assignment. We have defined a number of hard and soft constraints based on patient's requirements, ailments, preferences for a particular nurse, nurse's skill parameters, penalty, demands on duties, matching quotient with patient's requirements, location, etc. The assignment of nurses to patients for a particular shift depend on the relation between patient's need and the skill factor of the nurse, besides, of course, the availability factor of the nurse. This helps in achieving efficiency of the overall solution, besides properly supporting qualitative issues. In this regards, two objective functions are devised here to maximize the nurse's rewards and minimize the scheduling computational cost. The resulting algorithm has been tested on real-case scenarios of a nursing centre, providing evidence of the actual advantages of the proposed solution.

show abstract

“…Smet, et al [7], used an integer programming and introduced the concept of local and global consistency in the constraint evaluation process. In another study, Mujahid, et al [8] used an integer programming in the form of binary (0-1). Trilling, et al [9] suggested two methods to solve the scheduling problem for anesthetic nurse, that are integer programming and constraint programming.…”

Section: Related Literaturementioning

confidence: 99%

Nurse Scheduling Problem using Fuzzy Goal Programming with MINMAX Approach

2020

JIEC

View full text Add to dashboard Cite

Nurse scheduling is a complex issue since each nurse has its own work day and day off which needs to be managed. The non-singular hospital objectives, as well as the uncertainty of the objective value add to the complexity of this problem. In this article, nurse scheduling problems will be solved using Fuzzy Goal Programming with the MINMAX approach. The hospital’s objectives of optimizing the number of days off for nurses, the number of working days, evening shifts, and isolated work days can be achieved. The resulting solution from the computation process meets the specified deviation tolerance limits. Problem constraints regarding requests for nurse leave, the minimum number of nurses on duty per shift, restrictions on sequential working days, and other managerial rules can also be met. With the MINMAX approach, the imbalance between positive and negative deviation values can be overcome. In addition, sensitivity analysis is also easier to be done. This article contributes to the future by revealing that the use of fuzzy set theory with unbalanced positive and negative deviations can be effectively used in nurse scheduling problems. Thus, a satisfactory schedule which can meet nurse preferences and hospital policies can be made properly.

show abstract

Nurse Scheduling Problem: An Integer Programming Model with a Practical Application

Cited by 9 publications

References 16 publications

Sea lion attacking‐based deer hunting optimization algorithm for dynamic nurse scheduling in health care sector contribution of hybrid algorithm in cloud

Sea lion attacking‐based deer hunting optimization algorithm for dynamic nurse scheduling in health care sector contribution of hybrid algorithm in cloud

A Patient-Centric Nurse Scheduling Algorithm

Nurse Scheduling Problem using Fuzzy Goal Programming with MINMAX Approach

Contact Info

Product

Resources

About