This paper presents a multi-objective network design problem with environmental considerations for urban networks with queues. A spatial queuing link model is introduced to take account of the spatial effect of queuing. With this more realistic link performance function capturing spatial queuing, the network equilibrium flow patterns can be more accurately identified. Furthermore, to better estimate vehicle emissions, this paper proposes a refined emission estimation model, which distinguishes between travel speeds in free-running state and queue-forming state over a link. A multi-objective bi-level programming is then developed, in which the upper-level problem optimizes the investment decisions, whereas the lower-level problem characterizes the user equilibrium with spatial queuing delays. The metaheuristic of non-dominated sorting genetic algorithm II (NSGA-II) is adopted to solve the multi-objective network design problem. Numerical tests on the Sioux Falls network and the Barcelona network confirm the effectiveness of our proposed model and algorithm in identifying queuing equilibrium flows and Pareto optimal solutions. The refined models and valuable information about trade-offs among objectives are particularly helpful for environmentally sustainable transport network planning.

中文翻译：

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空间排队条件下的帕累托最优可持续交通网络设计

本文提出了一个多目标网络设计问题，其中考虑了带有队列的城市网络的环境问题。引入空间排队链接模型以考虑排队的空间效应。使用这种更实际的链路性能功能捕获空间排队，可以更准确地识别网络平衡流模式。此外，为了更好地估算车辆的排放，本文提出了一种改进的排放估算模型，该模型可以区分自由行驶状态下的行驶速度和形成链接的排队状态。然后开发了一个多目标的双层规划，其中上层问题优化了投资决策，而下层问题则以空间排队延迟为特征，描述了用户均衡。采用非主导排序遗传算法II（NSGA-II）的元启发式方法解决了多目标网络设计问题。在Sioux Falls网络和Barcelona网络上的数值测试证实了我们提出的模型和算法在识别排队均衡流和Pareto最优解方面的有效性。有关目标之间权衡的改进模型和有价值的信息对于环境可持续的运输网络规划特别有用。