ABSTRACT This paper extends the work on Pareto-improving hybrid rationing and pricing policy for general road networks by considering heterogeneous users with different values of time. Mathematical programming models are proposed to find a multiclass Pareto-improving pure road space rationing scheme (MPI-PR) and multiclass hybrid rationing and pricing schemes (MHPI and MHPI-S). A numerical example with a multimodal network is provided for comparing both the efficiency and equity of the three proposed policies. We discover that MHPI-S can achieve the largest reduction in total system delay, MHPI can induce the least spatial inequity and MHPI-S is a progressive policy which is appealing to policy makers. Furthermore, numerical results reveal that different classes of users react differently to the same hybrid policies and multiclass Pareto-improving hybrid schemes yield less delay reduction when compared to their single-class counterparts.

中文翻译：

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具有多类网络均衡的帕累托改进混合配给和定价策略

摘要 本文通过考虑具有不同时间价值的异构用户，扩展了一般道路网络的帕累托改进混合配给和定价政策的工作。提出了数学规划模型来寻找多类帕累托改进纯道路空间配给方案（MPI-PR）和多类混合配给和定价方案（MHPI 和 MHPI-S）。提供了一个具有多模式网络的数值示例，用于比较三种拟议政策的效率和公平性。我们发现 MHPI-S 可以最大程度地减少总系统延迟，MHPI 可以引起最少的空间不公平，并且 MHPI-S 是一种对决策者有吸引力的渐进政策。此外，