Multi-Start Iterated Local Search for the Mixed fleet Vehicle Routing Problem with Heterogeneous Electric Vehicles and Time-Dependent Charging Costs
Identifieur interne : 003388 ( Hal/Corpus ); précédent : 003387; suivant : 003389Multi-Start Iterated Local Search for the Mixed fleet Vehicle Routing Problem with Heterogeneous Electric Vehicles and Time-Dependent Charging Costs
Auteurs : Ons Sassi ; Wahiba Ramdane Cherif- Khettaf ; Ammar OulamaraSource :
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Abstract
This paper deals with a real world application that consists in the vehicle routing problem with mixed fleet of conventional and heterogenous electric vehicles including new constraints, denoted VRP-HFCC. This problem is defined by a set of customers that have to be served by a mixed fleet of vehicles composed of heterogenous fleet of Electric Vehicles (EVs) with distinct battery capacities and operating costs, and a set of identical Conventional Vehicles (CVs). The EVs could be charged during their trips in the available charging stations, which offer charging with a given technology of chargers and time dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are subject to the compatibility constraints with the available charging technologies and they could be partially charged. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and to minimize the total travel and charging costs. The developed multi-start algorithm is based on the Iterated Local Search metaheuristic which uses a Large Neighborhood Search with two different insertion strategies in the Local Search procedure. Different implementation schemes of the proposed method are tested on a set of real data instances with up to 550 customers as well as on generalized benchmark instances.
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This problem is defined by a set of customers that have to be served by a mixed fleet of vehicles composed of heterogenous fleet of Electric Vehicles (EVs) with distinct battery capacities and operating costs, and a set of identical Conventional Vehicles (CVs). The EVs could be charged during their trips in the available charging stations, which offer charging with a given technology of chargers and time dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are subject to the compatibility constraints with the available charging technologies and they could be partially charged. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and to minimize the total travel and charging costs. The developed multi-start algorithm is based on the Iterated Local Search metaheuristic which uses a Large Neighborhood Search with two different insertion strategies in the Local Search procedure. Different implementation schemes of the proposed method are tested on a set of real data instances with up to 550 customers as well as on generalized benchmark instances.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Multi-Start Iterated Local Search for the Mixed fleet Vehicle Routing Problem with Heterogeneous Electric Vehicles and Time-Dependent Charging Costs</title><author role="aut"><persName><forename type="first">Ons</forename><surname>Sassi</surname></persName><email></email><idno type="halauthor">1098151</idno><affiliation ref="#struct-44715"></affiliation></author><author role="aut"><persName><forename type="first">Wahiba</forename><surname>Ramdane Cherif- Khettaf</surname></persName><email></email><idno type="halauthor">1329554</idno><affiliation ref="#struct-44715"></affiliation></author><author role="aut"><persName><forename type="first">Ammar</forename><surname>Oulamara</surname></persName><email></email><idno type="halauthor">59436</idno></author><editor role="depositor"><persName><forename>WAHIBA</forename><surname>RAMDANE CHERIF-KHETTAF</surname></persName><email>ramdanec@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2016-04-25 17:40:51</date><date type="whenWritten">2015</date><date type="whenModified">2016-04-26 01:05:23</date><date type="whenReleased">2016-04-25 17:40:51</date><date type="whenProduced">2015</date></edition><respStmt><resp>contributor</resp><name key="339136"><persName><forename>WAHIBA</forename><surname>RAMDANE CHERIF-KHETTAF</surname></persName><email>ramdanec@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-01306896</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-01306896</idno><idno type="halBibtex">sassi:hal-01306896</idno><idno type="halRefHtml">series Lecture Notes in Computer Science,. Evolutionary Computation in Combinatorial Optimization, 9026 (pp 138-149.), Springer, 2015</idno><idno type="halRef">series Lecture Notes in Computer Science,. Evolutionary Computation in Combinatorial Optimization, 9026 (pp 138-149.), Springer, 2015</idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="LORIA-NSS" p="LORIA">Réseaux, systèmes et services</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno></seriesStmt><notesStmt><note type="audience" n="2">International</note><note type="popular" n="0">No</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Multi-Start Iterated Local Search for the Mixed fleet Vehicle Routing Problem with Heterogeneous Electric Vehicles and Time-Dependent Charging Costs</title><author role="aut"><persName><forename type="first">Ons</forename><surname>Sassi</surname></persName><idno type="halAuthorId">1098151</idno><affiliation ref="#struct-44715"></affiliation></author><author role="aut"><persName><forename type="first">Wahiba</forename><surname>Ramdane Cherif- Khettaf</surname></persName><idno type="halAuthorId">1329554</idno><affiliation ref="#struct-44715"></affiliation></author><author role="aut"><persName><forename type="first">Ammar</forename><surname>Oulamara</surname></persName><idno type="halAuthorId">59436</idno></author></analytic><monogr><title level="m">Evolutionary Computation in Combinatorial Optimization</title><editor>series Lecture Notes in Computer Science,</editor><imprint><publisher>Springer</publisher><biblScope unit="volume">9026</biblScope><biblScope unit="issue">pp 138-149.</biblScope><date type="datePub">2015</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">Vehicle routing problem </term><term xml:lang="en"> Electric vehicle charging </term><term xml:lang="en">Meta-heuristics</term><term xml:lang="en"> Iterated Local Search </term><term xml:lang="en"> Large Neighborhood Search </term><term xml:lang="en"> Optimization</term></keywords><classCode scheme="halDomain" n="info.info-ro">Computer Science [cs]/Operations Research [cs.RO]</classCode><classCode scheme="halTypology" n="COUV">Book section</classCode></textClass><abstract xml:lang="en">This paper deals with a real world application that consists in the vehicle routing problem with mixed fleet of conventional and heterogenous electric vehicles including new constraints, denoted VRP-HFCC. This problem is defined by a set of customers that have to be served by a mixed fleet of vehicles composed of heterogenous fleet of Electric Vehicles (EVs) with distinct battery capacities and operating costs, and a set of identical Conventional Vehicles (CVs). The EVs could be charged during their trips in the available charging stations, which offer charging with a given technology of chargers and time dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are subject to the compatibility constraints with the available charging technologies and they could be partially charged. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and to minimize the total travel and charging costs. The developed multi-start algorithm is based on the Iterated Local Search metaheuristic which uses a Large Neighborhood Search with two different insertion strategies in the Local Search procedure. Different implementation schemes of the proposed method are tested on a set of real data instances with up to 550 customers as well as on generalized benchmark instances.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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