Preference scheduling for nurses using column generation
Preference scheduling for nurses using column generation
复制标题
DOI：
10.1016/j.ejor.2003.06.046
复制
发表时间：
2005-07-16
影响因子：
6.4
通讯作者：
Purnomo, HW
中科院分区：
文献类型：
--
作者：
Bard, JF;Purnomo, HW
本文的目的是提出一种新的方法，调度护士，其中几个相互冲突的因素指导决策过程。与标准轮班和休息日是规则的制造设施不同，医院每周7天，每天24小时运营，并面临广泛波动的需求。需要更灵活地安排工作时间和休息日，特别是鉴于护士日益短缺。为了提高留用率，管理层现在必须以公平的方式考虑个人的偏好和休假要求，同时确保在任何时候都有足够的覆盖面。这个多目标问题的解决与列生成方法，结合整数规划和数学。整数规划制定为一组覆盖型问题，其列对应于替代时间表，护士可以在规划范围内工作。双交换启发式算法用于生成列。目标系数由护士的个人偏好被违反的程度来确定。作为计算方案的一部分，可行的解决方案进行了改进，以尽量减少外部护士的使用，但当覆盖范围存在差距时，外部护士尽可能均匀地分布在班次上。该方法进行了测试的一系列问题，多达100名护士使用的数据提供的一家大型医院在美国。结果表明，在大多数情况下，可以在几分钟内获得高质量的解决方案。(C)2004 Elsevier B.V.保留所有权利。
The purpose of this paper is to present a new methodology for scheduling nurses in which several conflicting factors guide the decision process. Unlike manufacturing facilities where standard shifts and days off are the rule, hospitals operate 24 hours a day, 7 days a week and face widely fluctuating demand. A more flexible arrangement for working hours and days off is needed, especially in light of the growing nursing shortage. To improve retention, management must now take into account individual preferences and requests for days off in a way that is perceived as fair, while ensuring sufficient coverage at all times. This multi-objective problem is solved with a column generation approach that combines integer programming and heuristics. The integer program is formulated as a set covering-type problem whose columns correspond to alternative schedules that a nurse can work over the planning horizon. A double swapping heuristic is used to generate the columns. The objective coefficients are determined by the degree to which the individual preferences of a nurse are violated. As part of the computational scheme, feasible solutions are refined to minimize the use of outside nurses, but when gaps in coverage exist, the outside nurses are distributed as evenly as possible over the shifts. The methodology was tested on a series of problems with up to 100 nurses using data provided by a large hospital in the US. The results indicate that high-quality solutions can be obtained within a few minutes in the majority of cases. (C) 2004 Elsevier B.V. All rights reserved.