Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/150168
Title: Optimizing Energy Consumption in Smart Cities’ Mobility: Electric Vehicles, Algorithms, and Collaborative Economy
Author: Ghorbani, Elnaz  
Fluechter, Tristan
Calvet Liñán, Laura  
Ammouriova, Majsa  
Panadero, Javier  
Juan, Angel A.  
Citation: Ghorbani, E. [Elnaz]. Fluechter, T. [Tristán]. Calvet, L. [Laura]. Ammouriova, M. [Majsa]. Panadero, J. [Javier]. Juan, A. [Angel]. A. (2023). Optimizing Energy Consumption in Smart Cities’ Mobility: Electric Vehicles, Algorithms, and Collaborative Economy. Energies 2023, 16, 1268. https://doi.org/10.3390/en16031268
Abstract: Mobility and transportation activities in smart cities require an increasing amount of energy. With the frequent energy crises arising worldwide and the need for a more sustainable and environmental friendly economy, optimizing energy consumption in these growing activities becomes a must. This work reviews the latest works in this matter and discusses several challenges that emerge from the aforementioned social and industrial demands. The paper analyzes how collaborative concepts and the increasing use of electric vehicles can contribute to reduce energy consumption practices, as well as intelligent x-heuristic algorithms that can be employed to achieve this fundamental goal. In addition, the paper analyzes computational results from previous works on mobility and transportation in smart cities applying x-heuristics algorithms. Finally, a novel computational experiment, involving a ridesharing example, is carried out to illustrate the benefits that can be obtained by employing these algorithms.
Keywords: energy consumption
mobility
transportation
smart cities
optimization
x-heuristics
DOI: https://doi.org/10.3390/en16031268
Document type: info:eu-repo/semantics/article
Version: info:eu-repo/semantics/publishedVersion
Issue Date: 25-Jan-2023
Publication license: http://creativecommons.org/licenses/by/3.0/es/  
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