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An Integer Decomposition Algorithm for Solving a Two-Stage Facility Location Problem with Second-Stage Activation Costs

机译:求解具有第二阶段激活成本的两阶段设施定位问题的整数分解算法

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We study a stochastic scenario-based facility location problem arising in situations when facilities must first be located, then activated in a particular scenario before they can be used to satisfy scenario demands. Unlike typical facility location problems, fixed charges arise in the initial location of the facilities, and then in the activation of located facilities. The first-stage variables in our problem are the traditional binary facility-location variables, whereas the second-stage variables involve a mix of binary facility-activation variables and continuous flow variables. Benders decomposition is not applicable for these problems due to the presence of the second-stage integer activation variables. Instead, we derive cutting planes tailored to the problem under investigation from recourse solution data. These cutting planes are derived by solving a series of specialized shortest path problems based on a modified residual graph from the recourse solution, and are tighter than the general cuts established by Laporte and Louveaux for two-stage binary programming problems. We demonstrate the computational efficacy of our approach on a variety of randomly generated test problems.
机译:我们研究了基于随机情景的设施位置问题,这种问题在必须首先定位设施然后在特定的情景中激活才能用于满足情景需求的情况下出现。与典型的设备位置问题不同,固定费用在设备的初始位置产生,然后在定位的设备激活时产生。我们问题中的第一阶段变量是传统的二元设施位置变量,而第二阶段变量涉及二元设施激活变量和连续流量变量的混合。由于第二阶段整数激活变量的存在,Benders分解不适用于这些问题。取而代之的是,我们从追索解决方案数据中得出针对所调查问题量身定制的切割平面。这些切平面是通过基于求和解中的修正残差图来解决一系列特殊的最短路径问题而得出的,并且比Laporte和Louveaux为两阶段二进制编程问题建立的一般切面更紧密。我们证明了我们的方法对各种随机生成的测试问题的计算效率。

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