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First-mile logistics parcel pickup: Vehicle routing with packing constraints under disruption.

Authors :
Giménez-Palacios, Iván
Parreño, Francisco
Álvarez-Valdés, Ramón
Paquay, Célia
Oliveira, Beatriz Brito
Carravilla, Maria Antónia
Oliveira, José Fernando
Source :
Transportation Research Part E: Logistics & Transportation Review. Aug2022, Vol. 164, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

First-mile logistics tackles the movement of products from retailers to a warehouse or distribution centre. This first step towards the end customer has been pushed by large e-commerce platforms forming extensive networks of partners and is critical for fast deliveries. First-mile pickup requires efficient methods different from those developed for last-mile delivery, among other reasons due to the complexity of cargo features and volume — increasing the relevance of advanced packing methods. More importantly, the problem is essentially dynamic and the pickup process, in which the vehicle is initially empty, is much more flexible to react to disruptions arising when the vehicles are en route. We model the static first-mile pickup problem as a vehicle routing problem for a heterogeneous fleet, with time windows and three-dimensional packing constraints. Moreover, we propose an approach to tackle the dynamic problem, in which the routes can be modified to accommodate disruptions — new customers' demands and modified requests of known customers that are arriving while the initially established routes are being covered. We propose three reactive strategies for addressing the disruptions depending on the number of vehicles available, and study their results on a newly generated benchmark for dynamic problems. The results allow quantifying the impact of disruptions depending on the strategy used and can help the logistics companies to define their own strategy, considering the characteristics of their customers and products and the available fleet. • A tool to plan the first-mile collection of parcels by a courier is provided. • Packing and shipping the products are jointly optimized. • Uncertainty caused by disruptions and changes is tackled. • Algorithms for static and dynamic VRPTW with packing constraints are proposed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13665545
Volume :
164
Database :
Academic Search Index
Journal :
Transportation Research Part E: Logistics & Transportation Review
Publication Type :
Academic Journal
Accession number :
158390970
Full Text :
https://doi.org/10.1016/j.tre.2022.102812