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dc.contributor.author | Torre-Martínez, María Rocío de la | es_ES |
dc.contributor.author | Corlu, Canan G. | es_ES |
dc.contributor.author | Faulin, Javier | es_ES |
dc.contributor.author | Onggo, Bahkti S. | es_ES |
dc.contributor.author | Juan, Angel A. | es_ES |
dc.date.accessioned | 2023-10-31T19:01:19Z | |
dc.date.available | 2023-10-31T19:01:19Z | |
dc.date.issued | 2021-02 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/199070 | |
dc.description.abstract | [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. | es_ES |
dc.description.sponsorship | 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. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Sustainability | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Transportation systems | es_ES |
dc.subject | Sustainability | es_ES |
dc.subject | Simulation | es_ES |
dc.subject | Optimization | es_ES |
dc.subject | Machine learning | es_ES |
dc.subject.classification | ORGANIZACION DE EMPRESAS | es_ES |
dc.subject.classification | ESTADISTICA E INVESTIGACION OPERATIVA | es_ES |
dc.title | Simulation, optimization, and machine learning in sustainable transportation systems: Models and applications | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/su13031551 | es_ES |
dc.relation.projectID | 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/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/Agencia Estatal de Investigación//RED2018-102642-T//Spanish Network in Intelligent and Sustainable Transportation . Spanish Ministry of Science, Innovation, and Universities/ | es_ES |
dc.relation.projectID | 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/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC// IoF2020-H2020 (731884)//Internet of Food and Farm 2020/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/731884/EU | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/Erasmus+//2019-I-ES01- KA103-062602/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Politécnica Superior de Alcoy - Escola Politècnica Superior d'Alcoi | es_ES |
dc.description.bibliographicCitation | Torre-Martínez, MRDL.; Corlu, CG.; Faulin, J.; Onggo, BS.; Juan, AA. (2021). Simulation, optimization, and machine learning in sustainable transportation systems: Models and applications. Sustainability. 13(3):1-21. https://doi.org/10.3390/su13031551 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/su13031551 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 21 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 13 | es_ES |
dc.description.issue | 3 | es_ES |
dc.identifier.eissn | 2071-1050 | es_ES |
dc.relation.pasarela | S\500832 | es_ES |
dc.contributor.funder | Erasmus+ | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |