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An Optimization Method for Coordinating Supplier Selection and Low-Carbon Design of Product Family

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An Optimization Method for Coordinating Supplier Selection and Low-Carbon Design of Product Family

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dc.contributor.author WANG, Q. es_ES
dc.contributor.author Tang, Dunbing es_ES
dc.contributor.author Yin, L. es_ES
dc.contributor.author Ullah, I. es_ES
dc.contributor.author Salido, M. A. es_ES
dc.contributor.author Giret Boggino, Adriana Susana es_ES
dc.date.accessioned 2020-03-16T14:46:54Z
dc.date.available 2020-03-16T14:46:54Z
dc.date.issued 2018-11 es_ES
dc.identifier.issn 1229-8557 es_ES
dc.identifier.uri http://hdl.handle.net/10251/138965
dc.description.abstract [EN] New stricter environmental regulations and consumer rising issues are making greenhouse gases (GHG) emission an increasing and urgent concern for manufacturing companies. Companies and researchers are seeking appropriate methods to reduce GHG emission of the manufactured products. Previous studies on low-carbon product design mainly concern on a single product. Currently, it is common to design a product family instead of a single product for increasing varieties to satisfy customers' requirements. Owing to the difference in design methods, the low-carbon design method for a single product cannot handle a product family. In addition, nowadays, the sourcing strategy is widely adopted by companies. A key problem of the procurement is supplier selection. The supplier selection affects not only profit but also GHG emission. However, it has not been simultaneously considered in low-carbon product design. In this article, an optimization model for coordinating low-carbon design of product family and supplier selection is proposed. In the model, the profit and the GHG emission of a product family are taken into consideration at the same time. Moreover, a genetic algorithm is developed to solve the established model. Finally, a case study is performed to verify the validity of the proposed approach. es_ES
dc.description.sponsorship This work was supported by National Natural Science Foundation of China [Grant number 51575264]; the Fundamental Research Funds for the Central Universities [Grant number 56XBA17006]; and Qin Lan Project. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof International Journal of Precision Engineering and Manufacturing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Low carbon es_ES
dc.subject Product family design es_ES
dc.subject Joint decision-making es_ES
dc.subject Supplier selection es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title An Optimization Method for Coordinating Supplier Selection and Low-Carbon Design of Product Family es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s12541-018-0199-4 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSFC//51575264/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Fundamental Research Funds for the Central Universities//56XBA17006/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Wang, Q.; Tang, D.; Yin, L.; Ullah, I.; Salido, MA.; Giret Boggino, AS. (2018). An Optimization Method for Coordinating Supplier Selection and Low-Carbon Design of Product Family. International Journal of Precision Engineering and Manufacturing. 19(11):1715-1726. https://doi.org/10.1007/s12541-018-0199-4 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s12541-018-0199-4 es_ES
dc.description.upvformatpinicio 1715 es_ES
dc.description.upvformatpfin 1726 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 19 es_ES
dc.description.issue 11 es_ES
dc.relation.pasarela S\375078 es_ES
dc.contributor.funder National Natural Science Foundation of China es_ES
dc.contributor.funder Fundamental Research Funds for the Central Universities es_ES
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