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dc.contributor.authorAntuchevičienė, Jurgita
dc.contributor.authorJafarnejad, Ahmad
dc.contributor.authorMahdiraji, Hannan Amoozad
dc.contributor.authorRazavi Hajiagha, Seyed Hossein
dc.contributor.authorKargar, Amir
dc.date.accessioned2023-09-18T20:23:01Z
dc.date.available2023-09-18T20:23:01Z
dc.date.issued2020
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/149437
dc.description.abstractIn the design of the supply chain, the use of the returned products and their recycling in the production and consumption network is called reverse logistics. The proposed model aims to optimize the flow of materials in the supply chain network (SCN), and determine the amount and location of facilities and the planning of transportation in conditions of demand uncertainty. Thus, maximizing the total profit of operation, minimizing adverse environmental effects, and maximizing customer and supplier service levels have been considered as the main objectives. Accordingly, finding symmetry (balance) among the profit of operation, the environmental effects and customer and supplier service levels is considered in this research. To deal with the uncertainty of the model, scenario-based robust planning is employed alongside a meta-heuristic algorithm (NSGA-II) to solve the model with actual data from a case study of the steel industry in Iran. The results obtained from the model, solving and validating, compared with actual data indicated that the model could optimize the objectives seamlessly and determine the amount and location of the necessary facilities for the steel industry more appropriately.eng
dc.formatPDF
dc.format.extentp. 1-23
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyChemical abstracts
dc.relation.isreferencedbyINSPEC
dc.relation.isreferencedbyDOAJ
dc.relation.isreferencedbyGenamics Journal Seek
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://www.mdpi.com/2073-8994/12/4/594
dc.source.urihttps://doi.org/10.3390/sym12040594
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:55309540/datastreams/MAIN/content
dc.titleRobust multi-objective sustainable reverse supply chain planning: an application in the steel industry
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references55
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.institutionUniversity of Tehran
dc.contributor.institutionUniversity of Tehran Coventry University
dc.contributor.institutionKhatam University
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.vgtuprioritizedfieldsFM0101 - Fizinių, technologinių ir ekonominių procesų matematiniai modeliai / Mathematical models of physical, technological and economic processes
dc.subject.ltspecializationsL104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies
dc.subject.enmulti-objective planning
dc.subject.enreverse supply chain
dc.subject.enrobust optimization
dc.subject.enuncertainty
dc.subject.enmeta-heuristic algorithm
dc.subject.ensteel making industry
dcterms.sourcetitleSymmetry
dc.description.issueiss. 4
dc.description.volumevol. 12
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi000540222200105
dc.identifier.doi10.3390/sym12040594
dc.identifier.elaba55309540


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