4.7 Article

Integrating first-mile pickup and last-mile delivery on shared vehicle routes for efficient urban e-commerce distribution

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trb.2019.09.013

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Continuum approximation; Pickup and delivery problems; Route efficiency; E-commerce distribution

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In this paper, we analyze the route efficiency trade-offs that emerge from combining first-mile pickup and last-mile delivery operations in an urban distribution system. We build on the extant literature on continuum approximation of optimal route distances and propose adjustment factors that account for the effects of integrated pickup and delivery operations. By means of comprehensive numerical experiments and regression analysis, we further propose a set of closed-form adjustment factors that improve existing continuum approximation-based route length estimations. These adjustment factors incorporate some non-trivial route efficiency trade-offs emerging from first-mile and last-mile integration that cannot easily be captured through continuum approximation. The proposed extensions are particularly relevant for the optimal strategic design and operational planning of large-scale, high-density last-mile distribution systems that are gaining in importance in light of e-commerce and omni-channel retailing. Our analyses suggest that the efficiency gains emerging from integrating first-mile pickup and last-mile delivery operations can be as high as 30%. However, the effective efficiency gains are sensitive to vehicle capacity constraints and other factors complicating the optimal stop sequence in integrated routes. We apply our proposed method to a real-world case study informed by operational data from one of India's largest e-commerce platforms for the city of Bengaluru. We find that by properly integrating its first-mile and last-mile operations, the company could reduce its urban traffic and emissions impact by up to 16%, while increasing the asset utilization and reducing the cost of operations of its vehicle fleet. (C) 2019 Elsevier Ltd. All rights reserved.

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