This paper studies a capacitated facility location problem under disruptions, where disruption risk not only diminishes facilities’ capacity partially or completely but also affects customers’ demand patterns. We use a budgeted uncertainty set to simultaneously capture facilities’ disruptions and customers’ uncertain demand caused by the failures of nearby facilities. Three two-stage robust optimization formulations with different objectives and performance bounds are built to model the problem. Both column-and-constraint generation algorithm and Benders decomposition method are implemented to solve the models. Numerical tests are conducted to study the impact of disruption correlated demand uncertainty and the performance of models and algorithms.

本文研究了在中断情况下有能力的设施选址问题，其中中断风险不仅会部分或完全减少设施的容量，而且还会影响客户的需求模式。我们使用预算不确定性集来同时捕获由附近设施故障引起的设施中断和客户的不确定需求。构建了三个具有不同目标和性能界限的两阶段鲁棒优化公式来对问题进行建模。列约束生成算法和Benders分解方法都被用来求解模型。进行数值测试以研究中断相关需求不确定性的影响以及模型和算法的性能。