Task assignment, pricing, and capacity planning for a hybrid fleet of centralized and decentralized couriers
Task assignment, pricing, and capacity planning for a hybrid fleet of centralized and decentralized couriers
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DOI：
10.1016/j.trc.2024.104533
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发表时间：
2024-03
期刊：
影响因子：
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通讯作者：
A. Behrendt;Martin Savelsbergh;He Wang
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文献类型：
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作者：
A. Behrendt;Martin Savelsbergh;He Wang
众包交付平台作为需要交付任务的消费者和进行这些交付的快递员之间的中介运作;两者都是不确定的。众包交付平台的主要挑战是满足其客户的服务水平（例如，95%准时交付），通过在时间窗口内动态送达交付任务。对于一个平台来说，两个关键的快递管理决策是如何安排快递员和如何向快递员分配交付任务。这两个决定可以是集中的（即，由平台决定）或分散的（即，由快递员决定）。集中这些决策会产生更可靠的劳动力，而分散这些决策可能会节省平台的成本，并允许快递员在决定何时何地工作方面有更多的自由。众包递送平台已经开始同时利用两种信使类型（即，混合系统），希望能够获得各自的优势。在本文中，我们解决了一个众包交付平台，利用集中式（承诺）和分散式（特设）快递的能力规划的挑战。我们提出了流体模型的输送系统使用任何类型的信使，和混合制剂。我们的理论，数值和模拟结果建立了一个混合系统的优越性，在大多数的现实世界的情况下，每个纯系统。
Crowdsourced delivery platforms operate as an intermediary between consumers who require delivery tasks and couriers who make these deliveries; both of which are uncertain. The main challenge of a crowdsourced delivery platform is to meet a service level for their customers (e.g., 95% on-time delivery) by serving dynamically arriving delivery tasks with time windows. The two critical courier management decisions for a platform are how to schedule couriers and how to assign delivery tasks to couriers. These two decisions can be centralized (i.e., decided by the platform) or decentralized (i.e., decided by the couriers). Centralizing these decisions produces a more reliable workforce while decentralizing them may come with cost savings to the platform and allows more freedom to couriers in deciding when and where to work. Crowdsourced delivery platforms have begun to utilize both courier types simultaneously (i.e., a hybrid system) with the hope of reaping the advantages of each. In this paper, we address the challenge of capacity planning for a crowdsourced delivery platform that utilizes both centralized (committed) and decentralized (ad-hoc) couriers. We present fluid models for delivery systems using either type of courier, and a hybrid formulation. Our theoretical, numerical, and simulation results establish the superiority of a hybrid system over each pure system in a majority of real-world scenarios.