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A matheuristic for the stochastic facility location problem

机译:随机设施定位问题的数学素描

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In this paper, we describe a matheuristic to solve the stochastic facility location problem which determines the location and size of storage facilities, the quantities of various types of supplies stored in each facility, and the assignment of demand locations to the open facilities, which minimize unmet demand and response time in lexicographic order. We assume uncertainties about demands, inventory spoilage, and transportation network availability. A good example where such a formulation makes sense is the the problem of pre-positioning emergency supplies, which aims to increase disaster preparedness by making the relief items readily available to people in need. The matheuristic employs iterated local search techniques to look for good location and inventory configurations, and uses CPLEX to optimize the assignments. Numerical experiments on a number of case studies and random instances for the pre-positioning problem demonstrate the effectiveness and efficiency of the matheuristic, which is shown to be particularly useful for tackling larger instances that are intractable for exact solvers. The matheuristic is therefore a contribution to the literature on heuristic approaches to solving facility location under uncertainties, can be used to further study the particular variant of the facility location problem, and can also support humanitarian logisticians in their planning of pre-positioning strategies.
机译:在本文中,我们描述了一种数学方法来解决随机设施选址问题,该问题决定了存储设施的位置和大小,每个设施中存储的各种类型的物资的数量,以及将需求位置分配给开放设施,从而以字典顺序最小化未满足的需求和响应时间。我们假设需求、库存损耗和运输网络可用性存在不确定性。这种表述有意义的一个很好的例子是预先安置应急物资的问题,其目的是通过向有需要的人随时提供救济物资来提高备灾能力。matheuristic采用迭代局部搜索技术寻找良好的位置和库存配置,并使用CPLEX优化分配。对预定位问题的大量案例研究和随机实例进行的数值实验证明了数学方法的有效性和效率,这对于解决精确解算器难以解决的较大实例尤其有用。因此,数学方法是对解决不确定条件下设施选址问题的启发式方法文献的贡献,可用于进一步研究设施选址问题的特定变量,也可支持人道主义后勤人员规划预定位策略。

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