This article studies a vehicle routing problem with environmental constraints that are motivated by the requirements for sustainable urban transport. The empirical research presents a fleet planning problem that takes into consideration both minimum cost vehicle routes and minimum pollution. The problem is formulated as a mixed integer linear programming model and experimentally validated using data collected from a real situation: a grocery company delivering goods ordered via e-channels to customers spread in the urban and metropolitan area of Genoa smart city. The proposed model is a variant of the vehicle routing problem tailored to include environmental issues and street limitations. Its novelty regards also the use of real data instances provided by the B2C grocery company. Managerial implications are the choice of both the routes and the number and type of vehicles. Results show that commercial distribution strategies achieve better results in term of both business and environmental performance, provided the smart mobility goals and constraints are included into the distribution model from the beginning.

中文翻译：

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智慧城市框架内配电网络中的运营管理。

本文研究了受可持续城市交通需求推动的具有环境约束的车辆路径问题。实证研究提出了一个车队规划问题，该问题既考虑了最低成本的车辆路线又考虑了最小的污染。该问题被公式化为混合整数线性规划模型，并使用从实际情况中收集的数据进行了实验验证：一家杂货公司通过电子渠道向热那亚智能城市的城市和大都市地区的客户提供了通过电子渠道订购的商品。拟议的模型是车辆路径问题的一种变体，旨在解决包括环境问题和街道限制在内的问题。它的新颖性还涉及到B2C杂货公司提供的真实数据实例的使用。对管理的影响是路线的选择以及车辆的数量和类型。结果表明，只要从一开始就将智能移动目标和约束条件纳入分销模型，商业分销策略就业务和环境绩效而言都将取得更好的结果。