Distributionally robust facility location problem under decision-dependent stochastic demand
Distributionally robust facility location problem under decision-dependent stochastic demand
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DOI：
10.1016/j.ejor.2020.11.002
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发表时间：
2021-03-07
影响因子：
6.4
通讯作者：
Shen, Siqian
中科院分区：
文献类型：
--
作者：
Basciftci, Beste;Ahmed, Shabbir;Shen, Siqian
虽然传统的设施选址问题考虑了外生需求，但在某些应用中，设施的位置可能会影响客户使用某些类型服务的意愿，例如，汽车共享，因此它们也影响随机需求的实现。此外，决策者可能不知道这种内生需求的确切分布以及它如何受到地点选择的影响。在本文中，我们考虑一个分布鲁棒设施选址问题，在其中我们解释随机需求的时刻作为设施选址决策的函数。我们重新制定了一个两阶段的决策相关的分布鲁棒优化模型作为一个整体的制定，然后推导出精确的混合整数线性规划的重新制定以及有效的不等式时，需求的均值和方差是分段线性函数的位置解决方案。我们进行了广泛的计算研究，我们比较我们的模型与决策相关的确定性模型，以及随机规划和分布鲁棒模型，没有决策相关的假设。结果表明，上级的性能，我们的方法与利润和服务质量的显着改善，在各种设置下，除了计算速度的配方增强。这些结果提请注意需要考虑的影响，在这个战略层面的规划问题的位置决策对客户需求。(C)2020爱思唯尔B.V.保留所有权利。
While the traditional facility location problem considers exogenous demand, in some applications, locations of facilities could affect the willingness of customers to use certain types of services, e.g., carsharing, and therefore they also affect realizations of random demand. Moreover, a decision maker may not know the exact distribution of such endogenous demand and how it is affected by location choices. In this paper, we consider a distributionally robust facility location problem, in which we interpret the moments of stochastic demand as functions of facility-location decisions. We reformulate a two-stage decision-dependent distributionally robust optimization model as a monolithic formulation, and then derive exact mixed-integer linear programming reformulation as well as valid inequalities when the means and variances of demand are piecewise linear functions of location solutions. We conduct extensive computational studies, in which we compare our model with a decision-dependent deterministic model, as well as stochastic programming and distributionally robust models without the decision-dependent assumption. The results show superior performance of our approach with remarkable improvement in profit and quality of service under various settings, in addition to computational speed-ups given by formulation enhancements. These results draw attention to the need of considering the impact of location decisions on customer demand within this strategic-level planning problem. (C) 2020 Elsevier B.V. All rights reserved.