Ghorbani, E.; Fluechter, T.; Calvet, L.; Ammouriova, M.; Panadero, J.; Juan, AA. (2023). Optimizing Energy Consumption in Smart Cities Mobility: Electric Vehicles, Algorithms, and Collaborative Economy. Energies. 16(3). https://doi.org/10.3390/en16031268
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/202783
Título:
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Optimizing Energy Consumption in Smart Cities Mobility: Electric Vehicles, Algorithms, and Collaborative Economy
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Autor:
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Ghorbani, Elnaz
Fluechter, Tristan
Calvet, Laura
Ammouriova, Majsa
Panadero, Javier
Juan, Angel A.
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Entidad UPV:
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Universitat Politècnica de València. Escuela Politécnica Superior de Alcoy - Escola Politècnica Superior d'Alcoi
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Fecha difusión:
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Resumen:
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[EN] 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, ...[+]
[EN] 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.
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Palabras clave:
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Energy consumption
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Mobility
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Transportation
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Smart cities
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Optimization
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X-heuristics
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Derechos de uso:
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Reconocimiento (by)
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Fuente:
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Energies. (eissn:
1996-1073
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DOI:
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10.3390/en16031268
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Editorial:
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MDPI AG
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Versión del editor:
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https://doi.org/10.3390/en16031268
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Código del Proyecto:
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111100RB-C21/ES/ALGORITMOS AGILES, INTERNET DE LAS COSAS, Y ANALITICA DE DATOS PARA UN TRANSPORTE SOSTENIBLE EN CIUDADES INTELIGENTES/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111100RB-C22/ES/MODELOS SOSTENIBLES Y ANALITICA DEL TRASPORTE EN CIUDADES INTELIGENTES/
info:eu-repo/grantAgreement/Erasmus+/2019-1-BG01-KA203-062602/EU/Building an innovative network for sharing of best educational practices, incl. game approach, in the area of international logistics and transport
info:eu-repo/grantAgreement/Fundació Bancària Caixa d'Estalvis i Pensions de Barcelona//21S09355-001/
info:eu-repo/grantAgreement/GVA//PROMETEO%2F2021%2F065/ES/Industrial Production and Logistics Optimization in Industry 4.0/i4OPT/
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Agradecimientos:
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This work has been partially funded by the Spanish Ministry of Science, Innovation, and Universities (PID2019-111100RB-C21-C22/AEI/10.13039/501100011033), the SEPIE Erasmus+ Program (2019-I-ES01-KA103-062602), the Barcelona ...[+]
This work has been partially funded by the Spanish Ministry of Science, Innovation, and Universities (PID2019-111100RB-C21-C22/AEI/10.13039/501100011033), the SEPIE Erasmus+ Program (2019-I-ES01-KA103-062602), the Barcelona City Council and Fundació ¿la Caixa¿ under the framework of the Barcelona Science Plan 2020-2023 (21S09355-001), and the Generalitat Valenciana (PROMETEO/2021/065).
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Tipo:
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Artículo
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