Optimizing energy consumption in smart cities’ mobility: electric vehicles, algorithms, and collaborative economy

Autor: Elnaz Ghorbani, Tristan Fluechter, Laura Calvet, Majsa Ammouriova, Javier Panadero, Angel A. Juan
Přispěvatelé: Universitat Politècnica de Catalunya. Departament d'Organització d'Empreses
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Energies
Volume 16
Issue 3
Pages: 1268
Popis: 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.
Databáze: OpenAIRE