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For solving the problem, the authors implemented L-shape algorithm and a computational case study is carried out on California state.    { \sf  \textbf{Verma and Gaukler} \cite{VermaGaukler2011} consider a stochastic version of the k-median optimization problem, which has applications in disaster management. In their proposed two-stage stochastic program, the location of the so-called relief distribution centers (RDCs) is determined as the first-stage variables followed by the computation of the flows of relief items from the RDCs to affected areas (AA), which form the second-stage variables. In particular, they consider an extension to the traditional k-median problems by allowing the \emph{performance} of each open RDC to vary depending on the distance from the center of the disaster (e.g., earthquake's epicenter). More precisely, the performance of each open RDC is a function of its distance from the disaster epicenter, where the function is obtained form available historical data. For the computational study, the authors consider acase study on an  earthquake scenario  in California state  and adopt their proposed two-stage model to a real-world problem. The the  resulting model is then solved by applying the classical L-Shaped method in stochastic programming framework. \\ \\ }