Bard Jonathan F, Purnomo Hadi W
Graduate Program in Operations Research & Industrial Engineering, I University Station C2200, The University of Texas, Austin, Texas 78712-0292, USA.
Health Care Manag Sci. 2006 Feb;9(1):71-85. doi: 10.1007/s10729-006-6281-y.
In many service organizations, rosters must be constructed weekly or monthly as demand and available personnel change. Once the permanent workforce is fixed, it may not be possible to alter its composition easily, implying that expensive contract labor may be the only option to cover shortages. With respect to nursing resources, this means calling in part-timers, casuals, or agency nurses on a daily basis, or hiring travelers for up to several months at a time. This paper addresses the latter option and presents two models that can be used to solve what we call the nurse addition problem. The first was originally developed to solve the midterm preference scheduling problem and is based on a pattern-view formulation. The second is derived from a shift-view formulation and is solved with a branch-and-price algorithm. In either case, the objective is to hire up to some predetermined number of nurses and assign them midterm schedules that minimize the maximum amount of uncovered shifts per day in the planning horizon. Each roster selected for a new nurse must satisfy a set of hard constraints related to the total working hours, workstretches, time between shifts, and weekend requirements, and a set of soft constraints related
在许多服务机构中，由于需求和可用人员不断变化，排班表必须每周或每月制定一次。一旦固定员工队伍确定下来，就不太可能轻易改变其构成，这意味着昂贵的合同工可能是弥补人员短缺的唯一选择。对于护理资源而言，这意味着每天都要召集兼职人员、临时工或中介护士，或者一次性雇佣几个月的临时护士。本文探讨后一种选择，并提出两种模型，可用于解决我们所称的护士补充问题。第一种模型最初是为解决中期偏好排班问题而开发的，基于模式视图公式。第二种模型源自班次视图公式，并通过分支定价算法求解。在任何一种情况下，目标都是雇佣一定数量的护士，并为他们安排中期排班表，以使计划期内每天未覆盖班次的最大数量最小化。为新护士选择的每个排班表都必须满足一组与总工作时间、工作时长、轮班间隔时间和周末要求相关的硬约束，以及一组相关的软约束。
