A variable neighborhood search based matheuristic for nurse rostering problems

Croce, Federico Della; Salassa, Fabio

doi:10.1007/s10479-012-1235-x

Cited by 50 publications

(27 citation statements)

References 16 publications

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“…The obtained results confirm previous academic results which have demonstrated the effectiveness of horizontal decomposition and the LBIH algorithm on other problems, e.g. the SMPTSP (Chapter 6) and the nurse rostering problem [40].…”

Section: Discussionsupporting

confidence: 88%

“…Despite possible differences between countries, the core problem remains the same: assign a shift or day-off to each nurse on each day of the scheduling period, taking into account a set of personal, organisational and legislative constraints. The academic literature offers many different solution techniques to this problem, ranging from exact methods [55,85] over metaheuristics [82,90] to hybrid approaches [40,118]. Although the problem has received considerable attention in the last decades, several important open issues remain in the academic literature.…”

Section: Introduction To Part I: Theorymentioning

confidence: 99%

“…This family of hybrid approaches recently gained significant attention because of their ability to solve problems for which traditional (meta)heuristics or exact approaches fail. Della Croce and Salassa [40] describe a variable neighbourhood search-based matheuristic for a real world nurse rostering problem. Neighbourhoods are defined by adding temporary constraints which fix a subset of heuristically selected assignments.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Nurse rostering: models and algorithms for theory, practice and integration with other problems

Smet

2016

4OR-Q J Oper Res

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Section: Discussionsupporting

confidence: 88%

Section: Introduction To Part I: Theorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nurse rostering: models and algorithms for theory, practice and integration with other problems

Smet

2016

4OR-Q J Oper Res

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“…The proposed approaches are mainly based on meta-heuristic algorithms [3,37,18], which are straightforward and effective for many practical problems. These range from Variable Neighbourhood Search [14,36] and Tabu Search [5] to Genetic Algorithms [1] and tailor-made heuristics [38,29]. However, meta-heuristic algorithms are not as efficient for problem instances where the structure of the problem is very complex, making it challenging to find a good-quality (or even a feasible) solution in a reasonable runtime.…”

Section: Introductionmentioning

confidence: 99%

A hybrid Integer Programming and Variable Neighbourhood Search algorithm to solve Nurse Rostering Problems

Rahimian

Akartunalı

Levine

2017

European Journal of Operational Research

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The Nurse Rostering Problem (NRP) is defined as assigning a number of nurses to different shifts during a specified planning period, considering some regulations and preferences. This is often very difficult to solve in practice particularly by applying a sole approach. In this paper, we propose a novel hybrid algorithm combining the strengths of Integer Programming (IP) and Variable Neighbourhood Search (VNS) algorithms to design a hybrid method for solving the NRP. After generating the initial solution using a greedy heuristic, the solution is further improved by employing a Variable Neighbourhood Descent algorithm. Then IP, deeply embedded in the VNS algorithm, is employed within a ruin-and-recreate framework to assist the search process. Finally, IP is called again to further refine the solution during the remaining time. We utilize the strength of IP not only to diversify the search process, but also to intensify the search efforts. To identify the quality of the current solution, we use a new generic scoring scheme to mark the low-penalty parts of the solution. Based on the computational tests with 24 instances recently introduced in the literature, we obtain better results with our proposed algorithm, where the hybrid algorithm outperforms two state-of-the-art algorithms and Gurobi in most of the instances. Furthermore, we introduce 11 randomly generated instances to further evaluate the efficiency of the hybrid algorithm, and we make these computationally challenging instances publicly available to other researchers for benchmarking purposes.

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“…Promising results were reported in comparison with a commercial genetic algorithm. Another matheuristic approach was reported in [16] for a NRP in an Italian private hospital. In this approach, 12 different neighbourhood structures were used.…”

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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A variable neighborhood search based matheuristic for nurse rostering problems

Cited by 50 publications

References 16 publications

Nurse rostering: models and algorithms for theory, practice and integration with other problems

Nurse rostering: models and algorithms for theory, practice and integration with other problems

A hybrid Integer Programming and Variable Neighbourhood Search algorithm to solve Nurse Rostering Problems

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

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