Academic Journal
Green hybrid fleets using electric vehicles: solving the heterogeneous vehicle routing problem with multiple driving ranges and loading capacities
| Τίτλος: | Green hybrid fleets using electric vehicles: solving the heterogeneous vehicle routing problem with multiple driving ranges and loading capacities |
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| Συγγραφείς: | Hatami, Sara, Eskandarpour, Majid, Chica, Manuel, Juan, Angel A., Ouelhadj, Djamila |
| Συνεισφορές: | Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3), Universidad de Granada, University of Portsmouth, Université de Lille, The University of Newcastle. Faculty of Engineering & Built Environment, School of Elect Engineering and Computer Science |
| Πηγή: | O2, repositorio institucional de la UOC Universitat Oberta de Catalunya (UOC) UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) SORT-Statistics and Operations Research Transactions; Vol. 44, Núm. 1 (2020): ; 141-170 SORT-Statistics and Operations Research Transactions; Vol 44, No 1 (2020): January-June; 141-170 oai:raco.cat:article/371186 Repositori Institucional de la Universitat Rovira i Virgili Universitat Rovira i virgili (URV) Dipòsit Digital de Documents de la UAB Universitat Autònoma de Barcelona |
| Στοιχεία εκδότη: | SORT: Statistics and Operations Research Transactions, 2020. |
| Έτος έκδοσης: | 2020 |
| Θεματικοί όροι: | Electric vehicles, Successive approximations method, Vehicles autònoms, mathematical programming::90C Mathematical programming, rangs múltiples de conducció, Sustainable Development Goals, Autonomous vehicles, Algorismes, rangos múltiples de conducción, Heterogeneous fleet, 90 Operations research, mathematical programming::90C Mathematical programming [Classificació AMS], Iterated greedy heuristic, Investigació operativa, problema de rutes de vehicles, Classificació AMS::62 Statistics::62P Applications, Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science, flotes heterogènies, iterated greedy heuristic, Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, Vehicle routing problem, 90 Operations research, mathematical programming::90B Operations research and management science [Classificació AMS], heterogeneous fleet, Programació (Matemàtica), Administració--Models matemàtics, vehículos eléctricos, SDG 7, vehicles elèctrics, electric vehicles, método de aproximaciones sucesivas, Classificació AMS::90 Operations research, multiple driving ranges, Vehículos autónomos, Estadística matemàtica--Aplicacions, heterogeneous fleets, 62 Statistics::62P Applications [Classificació AMS], mètode d'aproximacions successives, successive approximations method, Classificació AMS::90 Operations research, mathematical programming::90C Mathematical programming, 68 Computer science::68W Algorithms [Classificació AMS], Classificació AMS::68 Computer science::68W Algorithms, problema de rutas de vehículos, mathematical programming::90B Operations research and management science, Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC], flotas heterogéneas, Multiple driving ranges, vehicle routing problem |
| Περιγραφή: | The introduction of Electric Vehicles (EVs) in modern fleets facilitates green road transportation. However, the driving ranges of EVs are limited by the duration of their batteries, which arise new operational challenges. Hybrid fleets of gas and EVs might be heterogeneous both in loading capacities as well as in driving-range capabilities,whichmakes the design of efficient routing plans a difficult task. In this paper, we propose a newMulti-Round IteratedGreedy (MRIG) metaheuristic to solve the Heterogeneous Vehicle Routing Problem with Multiple Driving ranges and loading capacities (HeVRPMD). MRIG uses a successive approximations method to offer the decision maker a set of alternative fleet configurations,with different distance-based costs and green levels. The numerical experiments show that MRIG is able to outperform previous works dealing with the homogeneous version of the problem, which assumes the same loading capacity for all vehicles in the fleet. The numerical experiments also confirm that the proposed MRIG approach extends previous works by solving a more realistic HeVRPMD and provides the decision-maker with fleets with higher green levels. |
| Τύπος εγγράφου: | Article |
| Περιγραφή αρχείου: | application/pdf |
| DOI: | 10.2436/20.8080.02.98 |
| Σύνδεσμος πρόσβασης: | http://hdl.handle.net/10609/122027 http://hdl.handle.net/20.500.11797/RP4901 https://ddd.uab.cat/record/225690 https://dialnet.unirioja.es/servlet/articulo?codigo=7537022 https://ddd.uab.cat/pub/sort/sort_a2020v44n1/sort_a2020v44n1p141.pdf https://puredev.port.ac.uk/en/publications/green-hybrid-fleets-using-electric-vehicles-solving-the-heterogen https://ddd.uab.cat/record/225690 https://researchportal.port.ac.uk/portal/en/publications/green-hybrid-fleets-using-electric-vehicles(b2e6a095-3961-4cac-9e19-f7a350422bb9).html |
| Rights: | CC BY NC ND |
| Αριθμός Καταχώρησης: | edsair.dedup.wf.002..9c3d156dfc791a54d56396f9f96b67b9 |
| Βάση Δεδομένων: | OpenAIRE |
| DOI: | 10.2436/20.8080.02.98 |
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