A scenario-based robust optimization with a pessimistic approach for nurse rostering problem
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A scenario-based robust optimization with a pessimistic approach for nurse rostering problem Mohammad Reza Hassani1 · J. Behnamian1 Accepted: 1 November 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Nurse rostering problem (NRP) or nurse scheduling problem is a combinatorial optimization problem that involves the assignment of shifts to nurses while managing coverage constraints, expertise categories, labor legislation, contractual agreements, personal preferences, etc. The focus on this problem serves to improve service quality, nurse health and their satisfaction, and reduction of hospital costs. The existence of uncertainties and inaccurate estimates of the workload leads to a non-optimal or an infeasible solution. In this study, due to the importance of human resource management and crisis management in the health care system, a sustainable approach was developed with a robust scenario-based optimization method. Since NRP is a NP-hard problem, it is impossible to solve it in medium and large sizes in reasonable time. In this paper, a well-known metaheuristic algorithm, namely the differential evolution (DE) algorithm was proposed due to its sound structural features for searching in binary space. Then its performance was compared against the genetic algorithm. The results show that the DE algorithm has good performance. Keywords Nurse rostering problem · Scenario-based approach · Robust optimization · Differential evolution algorithm
1 Introduction For many service organizations, especially in the health care system, staff availability at the right time is an important factor in customer satisfaction (Arshad et al. 2012). On the other hand, the cost of health care systems is rising dramatically (Tanzi and Schuknecht 2000) and a significant part of these costs relates to the use of human resources. With an aging population quickly outpacing younger generations, the shortage of nurses
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J. Behnamian [email protected] Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
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Journal of Combinatorial Optimization
has increased the concern about health care systems in countries like Iran, Turkey, etc. (Darling et al. 2017). During the last 50 years, NRP has become a major issue in the field of operational research, and the role of intelligent management in this area has been highlighted across numerous research. The availability of automatic scheduling, however, can lead to improvements in hospital resource management, nurse and patient satisfaction, and thus reduce cost and administrative workload (Adoly et al. 2018). The nurse rostering problem is a subset of the workforce scheduling problem. This problem involves looking for a schedule that specifies the number of nurses needed with different expertise and the time they are serving on the planning horizon (Salassa and Vanden Berghe 2012). Solving a real case NRP manually often takes a lot of time and increases administrative workload. Due to the complexity of NRP, sign
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