An Integer Programming based Ant Colony Optimisation Method for Nurse Rostering

Bunton, Joe D.; Ernst, Andreas T.; Krishnamoorthy, Mohan

doi:10.15439/2017f237

Cited by 7 publications

(5 citation statements)

References 24 publications

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“…The shown results of the compared ejection chain heuristic and the branch and price algorithm are the results reported by the authors in [15]. The Gurobi solver results are the recent results reported in [8]. The results of the CP-ILS approach was reported in [25].…”

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confidence: 52%

“…A chemical reaction optimization heuristic was proposed in [35] for handling the NRP. In addition, there are multiple IP based heuristic solution approaches that were reported in literature, such as the IP based Ant Colony Optimization approach proposed in [8], where IP was used to facilitate finding feasible solutions for highly constrained problems. Another IP technique with improved cut generation strategies and primal heuristics was proposed in [29] and tested on instances of the First International Nurse Rostering Competition [21], revealing competitive performance to other heuristics.…”

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confidence: 99%

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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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confidence: 52%

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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“…The effectiveness of the method is examined by runs method in some different dimensions [4,12]. The dimension data is represented as number of nurses in this research, so we run our proposed method using a various number of nurses by using 50 number of ants, with several parameters such as a = 2, b = 1, evaporation rate = 0.2, and a large number of iterations 1000 to maximize the search procedure.…”

Section: Experiments Resultsmentioning

confidence: 99%

“…Jaradat et al [4] improve the elitist ant system with external memory, iterated local search, intensification mechanisms, and diversification mechanism. Bunton et al [12] improve ant colony optimization with integer programming to escape from local optima in ant colony optimization. Ant colony optimization will assign weight to each shift through the pheromone value, then the best shift is selected based on the pheromone value contained in one shift, then the integer programming will select the best solution.…”

Section: Introductionmentioning

confidence: 99%

Ant colony optimization with semi random initialization for nurse rostering problem

Achmad

Wibowo

Diana

2021

Int. J. Simul. Multidisci. Des. Optim.

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A nurse rostering problem is an NP-Hard problem that is difficult to solve during the complexity of the problem. Since good scheduling is the schedule that fulfilled the hard constraint and minimizes the violation of soft constraint, a lot of approaches is implemented to improve the quality of the schedule. This research proposed an improvement on ant colony optimization with semi-random initialization for nurse rostering problems. Semi-random initialization is applied to avoid violation of the hard constraint, and then the violation of soft constraint will be minimized using ant colony optimization. Semi-random initialization will improve the construction solution phase by assigning nurses directly to the shift that is related to the hard constraint, so the violation of hard constraint will be avoided from the beginning part. The scheduling process will complete by pheromone value by giving weight to the rest available shift during the ant colony optimization process. This proposed method is tested using a real-world problem taken from St. General Hospital Elisabeth. The objective function is formulated to minimize the violation of the constraints and balance nurse workload. The performance of the proposed method is examined by using different dimension problems, with the same number of ant and iteration. The proposed method is also compared to conventional ant colony optimization and genetic algorithm for performance comparison. The experiment result shows that the proposed method performs better with small to medium dimension problems. The semi-random initialization is a success to avoid violation of the hard constraint and minimize the objective value by about 24%. The proposed method gets the lowest objective value with 0,76 compared to conventional ant colony optimization with 124 and genetic algorithm with 1.

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“…Optimización de colonia de hormigas (Ant colony optimization -ACO). Este tipo de algoritmo es basado en el comportamiento de las colonias de hormigas y ha sido aplicado a problemas tales como asignación cuadrática, ruteo de vehículos, enrutamiento y muchos otros; es tanútil que ha sido aplicado a la optimización combinatoria para el tema de planificación grid [15,55].…”

Section: B Heurística Basada En La Poblaciónunclassified

Estrategias de planificación para datos y procesos en computación Grid: estado del arte

Bermúdez

Pérez

2019

Ing.USBMed

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Resumen. La distribución y la naturaleza compartida y heterogénea de la computación grid, hace que su objetivo de ofrecer aplicaciones con poder computacional colectivo, sea un gran reto. El objetivo es presentar el resultado de una investigación sistemática sobre aspectos teóricos de las temáticas que convergen en el diseño y desarrollo de planificadores de datos y procesos en computación grid. Se tomó como referente la metodología planteada para desarrollo de estados de arte, que cuenta con dos fases principales: heurística y hermenéutica. En el proceso se analizaron los fundamentos teóricos, tales como: la arquitectura, las etapas que conforman el proceso realizado por parte de un planificador grid y los tipos de planificación existentes, todo ello con el objeto de abordar los diferentes modelos y enfoques computacionales, heurísticos y metaheurísticos que permiten un funcionamiento eficiente y eficaz de maneraóptima de los planificadores grid, permitiendo mitigar en cierto grado los problemas presentados en la planificación grid. La optimización de la planificación de recursos grid, es unárea que se encuentra en desarrollo, dado que las problemáticas principales como: demora en la planificación y el proceso de optimización, están aún en etapa de desarrollo. Palabras Clave. Computación grid; heurística; metaheurística; planificación grid; procesos; trabajos.Abstract. The distribution, the shared and heterogeneous nature of grid computing, makes its objective of offering applications with a collective computational power, be a great challenge. The objetive is to present the result of the systematic research about theoretical aspects about converge topics in the design and development of data and process planners in GRID computation. The methodology proposed for the development of art states was taken as a reference, which has two main phases: heuristics and hermeneutics. In this process, the theoretical foundations are analyzed like the architecture, the stages that conforms the process performed by a GRID planner and the existing planner types; all this with the aim of addressing the different computational, heuristic and metaheuristic models and approaches that allows the efficient and effective operation of GRID planners, allowing to mitigate in certain degree the problems presented in GRID planning. The optimization of grid resource planning is an area that is under development, given that the main problems such as: delay in planning and the optimization process, are still in the development stage.

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An Integer Programming based Ant Colony Optimisation Method for Nurse Rostering

Cited by 7 publications

References 24 publications

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

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

Ant colony optimization with semi random initialization for nurse rostering problem

Estrategias de planificación para datos y procesos en computación Grid: estado del arte

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