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A Variable Neighbourhood Search for Nurse Scheduling with Balanced Preference Satisfaction

机译:可变邻域搜索护士调度,具有平衡偏好满意度

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The nurse scheduling problem (NSP) is a combinatorial optimisation problem widely tackled in the literature. Recently, a new variant of this problem was proposed, called nurse scheduling problem with balanced preference satisfaction (NSPBPS). This paper further investigates this variant of the NSP as we propose a new algorithm to solve the problem and obtain a better balance of overall preference satisfaction. Initiall, the algorithm converts the problem to a bottleneck assignment problem and solves it to generate an initial feasible solution for the NSPBPS. Posteriorly, the algorithm applies the Variable Neighbourhood Search (VNS) metaheuristic using two sets of search neighbourhoods in order to improve the initial solution. We empirically assess the performance of the algorithm using the NSPLib benchmark instances and we compare our results to other results found in the literature. The proposed VNS algorithm exhibits good performance by achieving solutions that are fairer (in terms of preference satisfaction) for the majority of the scenarios.
机译:护士调度问题(NSP)是在文献中广泛解决的组合优化问题。最近,提出了这种问题的新变种,称为护士调度问题,平衡偏好满意度(NSPBPS)。本文进一步调查了NSP的这种变体,因为我们提出了一种新的算法来解决问题并获得整体偏好满足的更好平衡。 initialL,该算法将问题转换为瓶颈分配问题,并解决了它以为NSPBPS生成初始可行的解决方案。然后,该算法使用两组搜索邻域应用变量邻域搜索(VNS)成群化,以便改善初始解决方案。我们经验使用NSPLIB基准实例统一地评估算法的性能,并将我们的结果与文献中的其他结果进行比较。通过实现大多数情况的解决方案,所提出的VNS算法通过实现更公平的解决方案(在偏好满意度)的解决方案。

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