论文标题
联合设施和需求位置问题
Joint Facility and Demand Location Problem
论文作者
论文摘要
在设施位置问题的典型应用中，人们认为需求的位置是该问题的输入。需求可能是固定的或动态的，但最终在优化器控制之外。相比之下，有一些设置，尤其是在人道主义背景下，优化器决定在哪里找到需求节点。在这项工作中，我们为联合设施和需求位置介绍了一个优化框架。作为我们一般框架的示例，我们将著名的K-Median和K-Center问题扩展到联合设施和需求位置问题（JFDLP），并将它们作为整数程序制定。我们建议基于网络流的本地搜索启发式。我们将启发式方法应用于飓风疏散响应案例研究。我们的结果表明了这些同时优化问题的挑战性质，尤其是在存在许多潜在位置的情况下。当潜在位置数量较大时，当地搜索启发式是最有希望的，而设施和需求节点的数量很少。
In typical applications of facility location problems, the location of demand is assumed to be an input to the problem. The demand may be fixed or dynamic, but ultimately outside the optimizers control. In contrast, there are settings, especially in humanitarian contexts, in which the optimizer decides where to locate a demand node. In this work, we introduce an optimization framework for joint facility and demand location. As examples of our general framework, we extend the well-known k-median and k-center problems into joint facility and demand location problems (JFDLP) and formulate them as integer programs. We propose a local search heuristic based on network flow. We apply our heuristic to a hurricane evacuation response case study. Our results demonstrate the challenging nature of these simultaneous optimization problems, especially when there are many potential locations. The local search heuristic is most promising when the the number of potential locations is large, while the number of facility and demand nodes to be located is small.
