The uncapacitated facility location problem (UFLP) is a popular NP-hard optimization problem that has been traditionally applied to logistics and supply networks, where decisions are difficult to reverse. However, over the years, many new application domains have emerged, in which real-time optimization is needed, such as Internet of Vehicles (IoV), virtual network functions placement, and network controller placement. IoV scenarios take into account the presence of multiple roadside units (RSUs) that should be frequently assigned to operating vehicles. To ensure the desired quality of service level, the allocation process needs to be carried out frequently and efficiently, as vehicles' demands change. In this dynamic environment, the mapping of vehicles to RSUs needs to be reoptimized periodically over time. Thus, this article proposes an agile optimization algorithm, which is tested using existing benchmark instances. The experiments show that it can efficiently generate high-quality and real-time results in dynamic IoV scenarios.

中文翻译：

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车联网网络中实时设施定位问题的敏捷优化

无容量设施位置问题 (UFLP) 是一种流行的NP-hard传统上应用于物流和供应网络的优化问题，其中决策难以逆转。然而，多年来，出现了许多需要实时优化的新应用领域，例如车联网（IoV）、虚拟网络功能放置和网络控制器放置。IoV 场景考虑了应经常分配给运营车辆的多个路边单元 (RSU) 的存在。为了确保所需的服务质量水平，分配过程需要随着车辆需求的变化而频繁且高效地执行。在这种动态环境中，车辆到 RSU 的映射需要随着时间的推移定期重新优化。因此，本文提出了一种敏捷优化算法，使用现有的基准测试实例进行测试。实验表明，它可以在动态 IoV 场景中高效地生成高质量和实时的结果。