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The Evolution of the Vehicle Routing Problem

A Survey of VRP Research and Practice from 2005 to 2022

Produktform: Buch / Einband - flex.(Paperback)

This book presents state-of-the-art research and practice in optimization routing, specifically the vehicle routing problem (VRP).   Since its introduction in the late 1950s, the VRP has been a very significant area of research and practice in operations research.  Vehicles are used to make deliveries and for pick-ups every day and everywhere.  Companies such as Amazon, UPS, FedEx, and DHL use route optimization to reduce mileage, fuel use, number of trucks on the road, and carbon dioxide emissions.  The authors compile and analyze 135 survey and review articles on vehicle routing topics published between 2005 and 2022 in an effort to make key observations about publication and trend history, summarize the overall contributions in the field, and identify trends in VRP research and practice.   The authors have compiled published research on models, algorithms, and applications for specific areas, including: alternative and multiple objectives; arc routing and general routing; drones, last-mile delivery, and urban distribution; dynamic and stochastic routing; green routing; inventory routing; loading constraints; location-routing; multiple depots; pickup and delivery and dial-a-ride problems; rich and multi-attribute routing; routing over time; shipping; two-echelon, collaborative, and inter-terminal problems; specific variants, benchmark datasets, and software; and exact algorithms and heuristics.  In addition, the book discusses how vehicle routing problems are among the most widely studied problems in combinatorial optimization due to the mathematical complexity and practical significance.weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Sprache(n): Englisch

ISBN: 978-3-031-18718-6 / 978-3031187186 / 9783031187186

Verlag: Springer International Publishing

Erscheinungsdatum: 03.01.2024

Seiten: 65

Auflage: 1

Autor(en): Bruce Golden, Xingyin Wang, Edward Wasil

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