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A stochastic model for operating room planning under uncertainty and equipment capacity constraints

机译:不确定性和设备容量约束下手术室计划的随机模型

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In the present economic context, the operating theater is considered as a critical activity in health care management. This paper describes a model for operating room (OR) planning under constraint of a unique equipment. At first level we schedule elective surgeries under the uncertainty of using a unique equipment. At the second level we consider emergency surgeries, and at the third level a coefficient factor for surgeons is introduced in using this unique equipment. The planning problem consists in scheduling a unique equipment and assigning elective cases to different periods over a planning horizon to minimize the sum of elective patient related costs and overtime costs of ORs. The most important factor that we have focused on this paper is equipment resource constraint. A new mathematical programming model is first proposed and at the second and third level, a new stochastic mathematical programming model is proposed. Then sample average approximation is presented to approximate the problem with sample size N and then Lingo is used as an exact approach. Because of NP-hardness, exact method does not work for large size problems, so a Metaheuristic approach (differential evolution) is proposed for large size problems. Numerical results show that important gains (approximately 3.5% in overall cost) can be realized by this stochastic OR planning model.
机译:在当前的经济背景下,手术室被认为是卫生保健管理中的关键活动。本文描述了一种在唯一设备约束下的手术室(OR)规划模型。在第一阶段,我们在使用独特设备的不确定性下安排了择期手术。在第二级,我们考虑急诊手术,在第三级,使用这种独特的设备引入了外科医生的系数系数。计划问题在于计划唯一的设备并在计划范围内将择期病例分配到不同时期,以最大程度地减少与病人有关的择期成本和OR的加班成本。我们在本文中关注的最重要因素是设备资源约束。首先提出了一种新的数学规划模型,并在第二和第三级提出了一种新的随机数学规划模型。然后提出样本平均近似值,以样本量N近似问题,然后将Lingo用作精确方法。由于NP硬度,精确方法不适用于大问题,因此提出了针对大问题的元启发式方法(微分演化)。数值结果表明,这种随机或计划模型可以实现重要的收益(约占总成本的3.5%)。

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