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Duman, Ece Naz; Tas, Duygu; Catay, Bulent
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/231798</identifier> <creators> <creator> <creatorName>Duman, Ece Naz</creatorName> <givenName>Ece Naz</givenName> <familyName>Duman</familyName> </creator> <creator> <creatorName>Tas, Duygu</creatorName> <givenName>Duygu</givenName> <familyName>Tas</familyName> <affiliation>MEF Univ, Fac Engn, Istanbul, Turkey</affiliation> </creator> <creator> <creatorName>Catay, Bulent</creatorName> <givenName>Bulent</givenName> <familyName>Catay</familyName> </creator> </creators> <titles> <title>Branch-And-Price-And-Cut Methods For The Electric Vehicle Routing Problem With Time Windows</title> </titles> <publisher>Aperta</publisher> <publicationYear>2021</publicationYear> <dates> <date dateType="Issued">2021-01-01</date> </dates> <resourceType resourceTypeGeneral="Text">Journal article</resourceType> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/231798</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1080/00207543.2021.1955995</relatedIdentifier> </relatedIdentifiers> <rightsList> <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract">In this paper, we address the electric vehicle routing problem with time windows and propose two branch-and-price-and-cut methods based on a column generation algorithm. One is an exact algorithm whereas the other is a heuristic method. The pricing sub-problem of the column generation method is solved using a label correcting algorithm. The algorithms are strengthened with the state-of-the-art acceleration techniques and a set of valid inequalities. The acceleration techniques include: (i) an intermediate column pool to prevent solving the pricing sub-problem at each iteration, (ii) a label correcting method employing the ng-route algorithm adopted to our problem, (iii) a bidirectional search mechanism in which both forward and backward labels are created, (iv) a procedure for dynamically eliminating arcs that connect customers to remote stations from the network during the path generation, (v) a bounding procedure providing early elimination of sub-optimal routes, and (vi) an integer programming model that generates upper bounds. Numerical experiments are conducted using a benchmark data set to compare the performances of the algorithms. The results favour the heuristic algorithm in terms of both the computational time and the number of instances solved. Moreover, the heuristic algorithm is shown to be specifically effective for larger instances. Both algorithms introduce a number of new solutions to the literature.</description> </descriptions> </resource>
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