Design of a Two-echelon Last-mile Delivery Model

Abstract

Due to high city congestion and growing demand for last-mile delivery services, several companies have been implemented two-echelon distribution strategies over the past few years. Notably, the installation of urban transshipment points has gained increasing attention, used by logistics operators to transfer goods from large freight trucks to smaller, more agile vehicles for last-mile delivery. Nevertheless, the main challenge is how to deciding the number and location of these facilities in the presence of demand uncertainty. In this paper, we develop a two-stage stochastic program to design two-echelon last-mile delivery networks under demand uncertainty. This approach decomposes the problem into strategic decisions (facility location) and operational decisions (daily distribution of goods). We solve the model through the sample average approximation technique to address large-scale instances and estimate the optimal routing costs using continuous approximation methods. Using a real-world case study with more than 1,300 customers from New York City, our results provide several managerial insights regarding the mix of transportation modes, facility location, and the impact of allowing the outsourcing of customer demand. We validate the results using a simulation-based approach that employs a deterministic Mixed-Integer Linear Program.