Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/62441
DC FieldValueLanguage
dc.contributor.authorMiguel, Fabioen_US
dc.contributor.authorFrutos, Marianoen_US
dc.contributor.authorTohme, Fernandoen_US
dc.contributor.authorMéndez Babey, Máximoen_US
dc.date.accessioned2020-01-21T09:43:45Z-
dc.date.available2020-01-21T09:43:45Z-
dc.date.issued2019en_US
dc.identifier.issn2169-3536en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/62441-
dc.description.abstractWe present an optimization procedure based on a hybrid version of an evolutionary multi-objective decision-making algorithm for its application in urban freight transportation planning problems. This tool is intended to solve the planning problems of a merchandise distribution firm that dispatches small volume fractional loads of fresh foods on daily schedules. The firm owns a network of distribution centers supplying a large number of small businesses in Buenos Aires and its surroundings. The recombination operator of the evolutionary algorithm used here has been designed specifically for this problem. It is intended to embody a strategy that takes into account constraints like temporary closeness, closeness time window and connectivity in order to improve its performance in the clustering phase. The representation allows incorporating specific information about the actual instances of the problem and uses adaptive control of the parameters in the calibration stage. The performance of the proposed optimizer was tested against the results obtained by two evolutionary algorithms, NSGA II and SPEA 2, widely used in similar problems. We use hypervolume as a measure of convergence and dispersion of Pareto fronts. The statistical analysis of the results obtained with the three algorithms uses the Wilcoxon rank sum test, which yields evidence that our procedure provides good results.en_US
dc.languageengen_US
dc.relation.ispartofIEEE Accessen_US
dc.sourceIEEE Access [ISSN 2169-3536], v. 7, p. 156707-156721en_US
dc.subject3329 Planificación urbanaen_US
dc.subject332907 Transporteen_US
dc.subject1207 Investigación operativaen_US
dc.subject120304 Inteligencia artificialen_US
dc.subject.otherDecision support systemsen_US
dc.subject.otherEvolutionary computationen_US
dc.subject.otherGenetic algorithmsen_US
dc.subject.otherLogisticsen_US
dc.subject.otherPareto optimizationen_US
dc.subject.otherRoad transportationen_US
dc.subject.otherUrban areasen_US
dc.titleA decision support tool for urban freight transport planning based on a multi-objective evolutionary algorithmen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ACCESS.2019.2949948en_US
dc.identifier.scopus85074635203-
dc.identifier.isi000497165400111-
dc.contributor.authorscopusid57023610800-
dc.contributor.authorscopusid24482935700-
dc.contributor.authorscopusid57203535337-
dc.contributor.authorscopusid57211622827-
dc.description.lastpage156721en_US
dc.identifier.issue8884163-
dc.description.firstpage156707en_US
dc.relation.volume7en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.contributor.daisngid3514340-
dc.contributor.daisngid31844332-
dc.contributor.daisngid30502946-
dc.contributor.daisngid9011687-
dc.description.numberofpages15en_US
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Miguel, F-
dc.contributor.wosstandardWOS:Frutos, M-
dc.contributor.wosstandardWOS:Tohme, F-
dc.contributor.wosstandardWOS:Babey, MM-
dc.date.coverdate2019en_US
dc.identifier.ulpgces
dc.description.sjr0,775
dc.description.jcr3,745
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
item.grantfulltextopen-
item.fulltextCon texto completo-
crisitem.author.deptGIR SIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0002-7133-7108-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameMéndez Babey, Máximo-
Appears in Collections:Artículos
Thumbnail
pdf
Adobe PDF (3,92 MB)
Show simple item record

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.