3.8 Proceedings Paper

A Rolling Horizon Auction Mechanism and Virtual Pricing of Shipping Capacity for Urban Consolidation Centers

Journal

COMPUTATIONAL LOGISTICS (ICCL 2015)
Volume 9335, Issue -, Pages 422-436

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-319-24264-4_29

Keywords

Rolling horizon; Virtual pricing; Urban consolidation center

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A number of cities around the world have adopted urban consolidation centers (UCCs) to address challenges of last-mile deliveries. At the UCC, goods are consolidated based on their destinations prior to their deliveries into city centers. Typically, a UCC owns a fleet of eco-friendly vehicles to carry out such deliveries. Shippers/carriers that make use of the UCC's service hence no longer need to be restricted by time-window and vehicle-type regulations. As a result, they retain the ability to deploy large trucks for the economies of scale from the source to the UCC which is located outside the city center. Furthermore, the resources which would otherwise be spent in the city center can then be utilized for other purposes. With possibly tighter regulation and thinning profit margin in near future, requests for UCC's services will become more and more common, and there is a need for a market mechanism to allocate UCC's resources to provide sustainable services for shippers/carriers in a win-win fashion. An early work of our research team (Handoko et al., 2014) proposed a profit-maximizing auction mechanism for the use of UCC's last-mile delivery service. In this paper, we extend this work with an idea of rolling horizon to give bidders more flexibility in competing for the UCC's resources in advance. In particular, it addresses the needs of many shippers/carriers to be able both plan deliveries weeks ahead and at the same time bid for the UCC's service at the last minute. Under our rolling horizon framework, the capacity of the same truck is up for bid in several successive auctions. To allocate truck capacities among these auctions under future demand uncertainty, we propose a virtual pricing mechanism which makes use of Target-oriented Robust Optimization techniques.

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