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Capacity Planning for Networks of Stem-Cell Donation Centers under Uncertainty

机译:不确定性下干细胞捐赠中心网络的容量规划

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Stem-cell transplantation is the last chance for patients of various blood-related diseases. Stem-cell donation centers admit patients in need of a stem-cell transplant and search for a perfect match between the patients and donors. The search process is time-consuming and requires expensive advanced equipments, in particular for DNA typing. In this study, we are concerned with a capacity planning problem in a network of stem-cell donation centers. The underlying optimization model integrates the operations for a donor search and aims to maximize the number of transplantations. A scenario-based stochastic programming approach is introduced to investigate the effect of the demand and service time variabilities into the capacity planning problem. We consider the maximum possible waiting time during the search process to obtain robust solutions against uncertainties. For this purpose, we approximate the maximum waiting time in the advanced blood testing with a robust queuing approach. The computational experiments are designed to illustrate the performance of the capacity planning model.
机译:干细胞移植是各种血液相关疾病患者的最后机会。干细胞捐赠中心接纳需要干细胞移植的患者,并寻求患者与捐赠者之间的完美匹配。搜索过程是耗时的并且需要昂贵的先进设备,特别是用于DNA分型。在这项研究中,我们关注干细胞捐赠中心网络中的容量规划问题。基本的优化模型整合了供体搜索的操作,旨在最大程度地提高移植数量。引入了一种基于场景的随机规划方法,以研究需求和服务时间可变性对容量规划问题的影响。我们考虑在搜索过程中的最大可能等待时间,以获得针对不确定性的可靠解决方案。为此,我们使用可靠的排队方法估算了高级血液测试中的最大等待时间。设计计算实验旨在说明容量规划模型的性能。

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