Simulation, optimization, and machine learning in sustainable transportation systems: Models and applications

[EN] The need for effective freight and human transportation systems has consistently increased during the last decades, mainly due to factors such as globalization, e-commerce activities, and mobility requirements. Traditionally, transportation systems have been designed with the main goal of reducing their monetary cost while offering a specified quality of service. During the last decade, however, sustainability concepts are also being considered as a critical component of transportation systems, i.e., the environmental and social impact of transportation activities have to be taken into account when managers and policy makers design and operate modern transportation systems, whether these refer to long-distance carriers or to metropolitan areas. This paper reviews the existing work on different scientific methodologies that are being used to promote Sustainable Transportation Systems (STS), including simulation, optimization, machine learning, and fuzzy sets. This paper discusses how each of these methodologies have been employed to design and efficiently operate STS. In addition, the paper also provides a classification of common challenges, best practices, future trends, and open research lines that might be useful for both researchers and practitioners.This work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities (PID2019-111100RB-C21-C22/AEI/10.13039/501100011033, RED2018-102642-T) and the SEPIE Erasmus+ Program (2019-I-ES01-KA103-062602), and the IoF2020-H2020 (731884) project.Torre-Martínez, MRDL.; Corlu, CG.; Faulin, J.; Onggo, BS.; Juan-Pérez, ÁA. (2021). Simulation, optimization, and machine learning in sustainable transportation systems: Models and applications. Sustainability. 13(3):1-21. https://doi.org/10.3390/su1303155112113

A Review of Big Data in Road Freight Transport Modeling: Gaps and Potentials

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A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification

The growth of environmental awareness and more robust enforcement of numerous regulations to reduce greenhouse gas (GHG) emissions have directed efforts towards addressing current environmental challenges. Considering the Vehicle Routing Problem (VRP), one of the effective strategies to control greenhouse gas emissions is to convert the fossil fuel-powered fleet into Environmentally Friendly Vehicles (EFVs). Given the multitude of constraints and assumptions defined for different types of VRPs, as well as assumptions and operational constraints specific to each type of EFV, many variants of environmentally friendly VRPs (EF-VRP) have been introduced. In this paper, studies conducted on the subject of EF-VRP are reviewed, considering all the road transport EFV types and problem variants, and classifying and discussing with a single holistic vision. The aim of this paper is twofold. First, it determines a classification of EF-VRP studies based on different types of EFVs, i.e., Alternative-Fuel Vehicles (AFVs), Electric Vehicles (EVs) and Hybrid Vehicles (HVs). Second, it presents a comprehensive survey by considering each variant of the classification, technical constraints and solution methods arising in the literature. The results of this paper show that studies on EF-VRP are relatively novel and there is still room for large improvements in several areas. So, to determine future insights, for each classification of EF-VRP studies, the paper provides the literature gaps and future research needs

Supply chain finance : a conceptual framework to advance research

Supply Chain Finance (SCF) arrangements aim to add value by taking a cooperative approach to financing in the supply chain. SCF has recently enjoyed considerable attention from industry, and providers of capital and technology are investing in platforms to facilitate new applications. A limited number of theoretical and empirical studies on the topic have been published. Current trends suggest, however, that the landscape of SCF is becoming increasingly complex and diverse. We describe some key developments and their implications for firms that (may) implement an SCF arrangement. In particular, we show that strategic and tactical considerations may impact the value of these arrangements. Failure to recognize alternatives and associated trade-offs may entail missed opportunities for firms. We present a framework that positions SCF concepts and shows the need for further research. We conclude with observations on managerial relevance

Exploring the Role of Natural Gas in U.S. Trucking (Revised Version)

The recent emergence of natural gas as an abundant, inexpensive fuel in the United States could prompt a momentous shift in the level of natural gas utilized in the transportation sector. The cost advantage of natural gas vis-à-vis diesel fuel is particularly appealing for vehicles with a high intensity of travel and thus fuel use. Natural gas is already a popular fuel for municipal and fleet vehicles such as transit buses and taxis. In this paper, we investigate the possibility that natural gas could be utilized to provide fuel cost savings, geographic supply diversity and environmental benefits for the heavy-duty trucking sector and whether it can enable a transition to lower carbon transport fuels. We find that a small, cost-effective intervention in markets could support a transition to a commercially sustainable natural gas heavyduty fueling system in the state of California and that this could also advance some of the state’s air quality goals. Our research shows that an initial advanced natural gas fueling system in California could facilitate the expansion to other U.S. states. Such a network would enable a faster transition to renewable natural gas or biogas and waste-to-energy pathways. Stricter efficiency standards for natural gas Class 8 trucks and regulation of methane leakage along the natural gas supply chain would be necessary for natural gas to contribute substantially to California’s climate goals as a trucking fuel. To date, industry has favored less expensive technologies that do not offer the highest level of environmental performance