Rapid urban growth, the increasing importance of e‐commerce and high consumer service expectations have given rise to new and innovative models for freight delivery within urban environments. Crowdsourced solutions—where drivers are not employed by a carrier but occasionally offer their services through on‐line platforms and are contracted as required by carriers—are receiving growing attention from industry. We consider a crowdsourced system where drivers express their availability to perform delivery tasks for a given period of time and the platform communicates a schedule with requests to serve. We investigate the potential benefits of introducing transfers to support driver activities. At transfer locations, drivers can drop off packages for pick up by other drivers at a later time. We frame the problem as a multidepot pickup and delivery problem with time windows and transfers, and propose an adaptive large neighborhood search algorithm that effectively identifies beneficial transfer opportunities and synchronizes driver operations. Computational experiments indicate that introducing transfer options can significantly reduce system‐wide travel distance as well as the number of drivers required to serve a given set of requests, especially when drivers have short availability and requests have high service requirements.

中文翻译：

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具有众包司机的交付系统：转移的取件和交付问题

快速的城市发展、电子商务的重要性日益增加以及对消费者服务的高期望已经催生了城市环境中的新型货运交付模式。众包解决方案——司机不是受雇于承运人，而是偶尔通过在线平台提供服务，并根据承运人的要求签订合同——越来越受到业界的关注。我们考虑一个众包系统，其中司机表达他们在给定时间段内执行交付任务的可用性，并且平台将时间表与服务请求进行沟通。我们调查了引入转移以支持司机活动的潜在好处。在中转地点，司机可以将包裹投递给其他司机稍后取件。我们将问题构建为具有时间窗口和换乘的多站取货和配送问题，并提出了一种自适应大型邻域搜索算法，可有效识别有利的换乘机会并同步驾驶员操作。计算实验表明，引入换乘选项可以显着减少系统范围内的行驶距离以及为一组给定的请求提供服务所需的司机数量，尤其是当司机的可用性很短而请求有很高的服务要求时。