Multi-objective green mixed vehicle routing problem under rough environment

This paper proposes a multi-objective Green Vehicle Routing Problem (G-VRP) considering two types of vehicles likely company-owned vehicle and third-party logistics in the imprecise environment. Focusing only on one objective, especially the distance in the VRP is not always right in the sustainabil...

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Autores principales:	Joydeep Dutta, Partha Sarathi Barma, Anupam Mukherjee, Samarjit Kar, Tanmay De, Dragan Pamučar, Šarūnas Šukevičius, Giedrius Garbinčius
Formato:	article
Lenguaje:	EN
Publicado:	Vilnius Gediminas Technical University 2021
Materias:	green vrp multi-objective vrp evolutionary methods nsga-ii vikor sustainability Transportation engineering TA1001-1280
Acceso en línea:	https://doaj.org/article/edbc94a1b4f14955abb16d71b9bcdd22
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id	oai:doaj.org-article:edbc94a1b4f14955abb16d71b9bcdd22
record_format	dspace
spelling	oai:doaj.org-article:edbc94a1b4f14955abb16d71b9bcdd222021-11-25T13:02:48ZMulti-objective green mixed vehicle routing problem under rough environment1648-41421648-348010.3846/transport.2021.14464https://doaj.org/article/edbc94a1b4f14955abb16d71b9bcdd222021-02-01T00:00:00Zhttps://journals.vgtu.lt/index.php/Transport/article/view/14464https://doaj.org/toc/1648-4142https://doaj.org/toc/1648-3480This paper proposes a multi-objective Green Vehicle Routing Problem (G-VRP) considering two types of vehicles likely company-owned vehicle and third-party logistics in the imprecise environment. Focusing only on one objective, especially the distance in the VRP is not always right in the sustainability point of view. Here we present a bi-objective model for the G-VRP that can address the issue of the emission of GreenHouse Gases (GHGs). We also consider the demand as a rough variable. This paper uses the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to solve the proposed model. Finally, it uses Multicriteria Optimization and Compromise Solution (abbreviation in Serbian – VIKOR) method to determine the best alternative from the Pareto front. First published online 25 February 2021Joydeep DuttaPartha Sarathi BarmaAnupam MukherjeeSamarjit KarTanmay DeDragan PamučarŠarūnas ŠukevičiusGiedrius GarbinčiusVilnius Gediminas Technical Universityarticlegreen vrpmulti-objective vrpevolutionary methodsnsga-iivikorsustainabilityTransportation engineeringTA1001-1280ENTransport, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	green vrp multi-objective vrp evolutionary methods nsga-ii vikor sustainability Transportation engineering TA1001-1280
spellingShingle	green vrp multi-objective vrp evolutionary methods nsga-ii vikor sustainability Transportation engineering TA1001-1280 Joydeep Dutta Partha Sarathi Barma Anupam Mukherjee Samarjit Kar Tanmay De Dragan Pamučar Šarūnas Šukevičius Giedrius Garbinčius Multi-objective green mixed vehicle routing problem under rough environment
description	This paper proposes a multi-objective Green Vehicle Routing Problem (G-VRP) considering two types of vehicles likely company-owned vehicle and third-party logistics in the imprecise environment. Focusing only on one objective, especially the distance in the VRP is not always right in the sustainability point of view. Here we present a bi-objective model for the G-VRP that can address the issue of the emission of GreenHouse Gases (GHGs). We also consider the demand as a rough variable. This paper uses the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to solve the proposed model. Finally, it uses Multicriteria Optimization and Compromise Solution (abbreviation in Serbian – VIKOR) method to determine the best alternative from the Pareto front. First published online 25 February 2021
format	article
author	Joydeep Dutta Partha Sarathi Barma Anupam Mukherjee Samarjit Kar Tanmay De Dragan Pamučar Šarūnas Šukevičius Giedrius Garbinčius
author_facet	Joydeep Dutta Partha Sarathi Barma Anupam Mukherjee Samarjit Kar Tanmay De Dragan Pamučar Šarūnas Šukevičius Giedrius Garbinčius
author_sort	Joydeep Dutta
title	Multi-objective green mixed vehicle routing problem under rough environment
title_short	Multi-objective green mixed vehicle routing problem under rough environment
title_full	Multi-objective green mixed vehicle routing problem under rough environment
title_fullStr	Multi-objective green mixed vehicle routing problem under rough environment
title_full_unstemmed	Multi-objective green mixed vehicle routing problem under rough environment
title_sort	multi-objective green mixed vehicle routing problem under rough environment
publisher	Vilnius Gediminas Technical University
publishDate	2021
url	https://doaj.org/article/edbc94a1b4f14955abb16d71b9bcdd22
work_keys_str_mv	AT joydeepdutta multiobjectivegreenmixedvehicleroutingproblemunderroughenvironment AT parthasarathibarma multiobjectivegreenmixedvehicleroutingproblemunderroughenvironment AT anupammukherjee multiobjectivegreenmixedvehicleroutingproblemunderroughenvironment AT samarjitkar multiobjectivegreenmixedvehicleroutingproblemunderroughenvironment AT tanmayde multiobjectivegreenmixedvehicleroutingproblemunderroughenvironment AT draganpamucar multiobjectivegreenmixedvehicleroutingproblemunderroughenvironment AT sarunassukevicius multiobjectivegreenmixedvehicleroutingproblemunderroughenvironment AT giedriusgarbincius multiobjectivegreenmixedvehicleroutingproblemunderroughenvironment
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Multi-objective green mixed vehicle routing problem under rough environment

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