The worldwide trend of urbanization, the rising needs of individuals, and the continuous growth of e-commerce lead to increasing urban delivery activities, which are a substantial driver of traffic and pollution in cities. Due to rising public pressure, emission-reducing measures are increasingly likely to be introduced. Such measures can cover diesel bans or even entire car-free zones, causing drastic effects on delivery networks in urban areas. As an option to reduce the risk of a regulation-induced shock, we present a resilience-oriented network and fleet optimization. We propose an innovative parcel delivery concept for last mile delivery (LMD) operations and develop an optimization model to support tactical planning decisions. Our model minimizes overall operating costs by determining optimal locations for micro depots and it allocates transport vehicles to them. An adjustable CO₂-threshold and external costs are included to consider potential regulatory restrictions by city authorities. We implement our model into a decision support system (DSS) that allows analyzing and comparing different scenarios. We provide a computational study by evaluating and discussing our DSS with an example of a mid-sized German city. Our results and findings demonstrate the trade-off between cost and emission minimization by quantifying the impacts of various fleet compositions. The proposed logistics concept represents an option to achieve environmentally friendly, cost-efficient, and resilient LMD of parcels.

世界范围的城市化趋势，个人需求的增长以及电子商务的持续增长导致城市交付活动的增加，这是城市交通和污染的重要推动力。由于公众压力的增加，越来越有可能采取减少排放的措施。这些措施可能覆盖柴油禁令，甚至覆盖整个无车区，对市区的运输网络造成巨大影响。作为减少规章引起的电击风险的一种选择，我们提出了一种以弹性为导向的网络和车队优化方案。我们为“最后一英里”交付（LMD）操作提出了一种创新的包裹交付概念，并开发了一种优化模型来支持战术计划决策。我们的模型通过确定微型仓库的最佳位置来最大程度地降低总体运营成本，并为其分配运输工具。可调CO_包括2阈值和外部成本，以考虑城市当局的潜在监管限制。我们将模型实施到决策支持系统（DSS）中，该系统可以分析和比较不同的方案。通过评估和讨论我们的DSS（以德国中型城市为例），我们提供了计算研究。我们的结果和发现通过量化各种车队组成的影响，证明了成本与排放最小化之间的权衡。提出的物流概念代表了实现环保，成本效益和包裹性LMD的一种选择。