4.4 Article

The last-mile vehicle routing problem with delivery options

期刊

OR SPECTRUM
卷 43, 期 4, 页码 877-904

出版社

SPRINGER
DOI: 10.1007/s00291-021-00633-0

关键词

Routing; Vehicle routing; City logistics; Branch-price-and-cut; Service level

资金

  1. Deutsche Forschungsgemeinschaft (DFG) [IR 122/8-1]

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The ongoing rise in e-commerce has increased the number of first-time delivery failures, resulting in rework and impacting carriers' delivery costs. A new vehicle routing problem with delivery options (VRPDO) is introduced to minimize costs and reach a specified service level based on customer preferences, with a focus on respecting capacities when assigning shipments. A new branch-price-and-cut algorithm is presented for solving the VRPDO and optimal solutions are provided for instances with up to 100 delivery options.
The ongoing rise in e-commerce comes along with an increasing number of first-time delivery failures due to the absence of the customer at the delivery location. Failed deliveries result in rework which in turn has a large impact on the carriers' delivery cost. In the classical vehicle routing problem (VRP) with time windows, each customer request has only one location and one time window describing where and when shipments need to be delivered. In contrast, we introduce and analyze the vehicle routing problem with delivery options (VRPDO), in which some requests can be shipped to alternative locations with possibly different time windows. Furthermore, customers may prefer some delivery options. The carrier must then select, for each request, one delivery option such that the carriers' overall cost is minimized and a given service level regarding customer preferences is achieved. Moreover, when delivery options share a common location, e.g., a locker, capacities must be respected when assigning shipments. To solve the VRPDO exactly, we present a new branch-price-and-cut algorithm. The associated pricing subproblem is a shortest-path problem with resource constraints that we solve with a bidirectional labeling algorithm on an auxiliary network. We focus on the comparison of two alternative modeling approaches for the auxiliary network and present optimal solutions for instances with up to 100 delivery options. Moreover, we provide 17 new optimal solutions for the benchmark set for the VRP with roaming delivery locations.

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