Mathematical Models and Algorithms for Large-Scale Transportation Problems

Carlos A. S. Oliveira ()
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Carlos A. S. Oliveira: AT&T Labs Inc.

Chapter Chapter 4 in Handbook of Artificial Intelligence and Data Sciences for Routing Problems, 2025, pp 69-91 from Springer

Abstract: Abstract Intermodal transportation, also known as intermodal shipping or freight transport, involves moving goods using multiple transportation modes like trucks, trains, ships, and airplanes, with standardized containers facilitating seamless transfers without unloading and reloading cargo. This method offers several industrial benefits, including increased efficiency, cost savings, environmental advantages, and improved reliability. Efficiency is enhanced through reduced delays and minimized handling, while cost savings arise from optimizing various modes and routes. Environmentally, it is more sustainable, as trains and ships are more fuel-efficient and emit less pollution than long-haul trucking. Additionally, intermodal transportation reduces road congestion and highway wear by shifting long-haul transport to railways or waterways, and offers greater reliability by mitigating traffic and road closure impacts. In this paper, we consider a class of problems that occur by the interaction of two or more transportation modes, as used in intermodal transportation.

Keywords: Optimization; Intermodal transportation; Routing efficiency; Machine learning (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-78262-6_4

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