This paper studies a real-time parking-sharing program with which owners of private parking spaces can lend out their parking spaces to other drivers to park when these are not in use. Compared with curbside and garage parking problems, the information of supplies and demands is randomly announced by drivers and owners respectively via a parking-sharing APP installed on their smartphones. Besides, the parking spaces made available by independent owners are usually heterogeneous in terms of their locations and available time intervals. Thus, two critical issues need to be resolved: (a) appropriately matching demands and supplies under an uncertain setting; and (b) efficiently scheduling the demands matched to avoid potential parking conflicts. We propose a novel real-time reservation approach based on a rolling-horizon framework, which can assign multiple drivers to a single parking space in order to better utilize scarce parking resources. For each period, an integrated optimal matching-and-scheduling problem is formulated as a mixed integer programming model and proved to be strongly NP-hard. To fast generate a near-optimal solution to the problem, a two-stage heuristics derived from the minimum-cost flow problem is developed. The computational results validate the efficiency and effectiveness of the proposed approach. Some operational insights are also presented and discussed.

中文翻译：

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实时私人停车共享程序的两阶段匹配调度算法

本文研究了一个实时停车共享程序，通过该程序，私人停车位的所有者可以在不使用时将其停车位借给其他司机停车。与路边和车库停车问题相比，供求信息是由司机和车主分别通过安装在智能手机上的停车共享APP随机发布的。此外，独立业主提供的停车位通常在位置和可用时间间隔方面存在差异。因此，需要解决两个关键问题：(a) 在不确定的环境下适当匹配需求和供应；(b) 有效地调度匹配的需求以避免潜在的停车冲突。我们提出了一种基于滚动水平框架的新型实时预订方法，它可以将多个司机分配到一个停车位，以便更好地利用稀缺的停车资源。对于每个时期，一个集成的最优匹配和调度问题被表述为混合整数规划模型，并被证明是强 NP 难的。为了快速生成问题的近乎最优解，开发了从最小成本流问题导出的两阶段启发式算法。计算结果验证了所提出方法的效率和有效性。还介绍和讨论了一些运营见解。为了快速生成问题的近乎最优解，开发了从最小成本流问题导出的两阶段启发式算法。计算结果验证了所提出方法的效率和有效性。还介绍和讨论了一些运营见解。为了快速生成问题的近乎最优解，开发了从最小成本流问题导出的两阶段启发式算法。计算结果验证了所提出方法的效率和有效性。还介绍和讨论了一些运营见解。