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A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain

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A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain

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dc.contributor.author Díaz-Madroñero Boluda, Francisco Manuel es_ES
dc.contributor.author Peidro Payá, David es_ES
dc.contributor.author Mula, Josefa es_ES
dc.date.accessioned 2015-06-10T08:48:38Z
dc.date.available 2015-06-10T08:48:38Z
dc.date.issued 2014-12-01
dc.identifier.issn 0307-904X
dc.identifier.uri http://hdl.handle.net/10251/51465
dc.description.abstract We consider a real-world automobile supply chain in which a first-tier supplier serves an assembler and determines its procurement transport planning for a second-tier supplier by using the automobile assembler's demand information, the available capacity of trucks and inventory levels. The proposed fuzzy multi-objective integer linear programming model (FMOILP) improves the transport planning process for material procurement at the first-tier supplier level, which is subject to product groups composed of items that must be ordered together, order lot sizes, fuzzy aspiration levels for inventory and used trucks and uncertain truck maximum available capacities and minimum percentages of demand in stock. Regarding the defuzzification process, we apply two existing methods based on the weighted average method to convert the FMOILP into a crisp MOILP to then apply two different aggregation functions, which we compare, to transform this crisp MOILP into a single objective MILP model. A sensitivity analysis is included to show the impact of the objectives weight vector on the final solutions. The model, based on the full truck load material pick method, provides the quantity of products and number of containers to be loaded per truck and period. An industrial automobile supply chain case study demonstrates the feasibility of applying the proposed model and the solution methodology to a realistic procurement transport planning problem. The results provide lower stock levels and higher occupation of the trucks used to fulfill both demand and minimum inventory requirements than those obtained by the manual spreadsheet-based method. (C) 2014 Elsevier Inc. All rights reserved. es_ES
dc.description.sponsorship This work has been funded partly by the Spanish Ministry of Science and Technology project: Production technology based on the feedback from production, transport and unload planning and the redesign of warehouses decisions in the supply chain (Ref. DPI2010-19977) and by the Universitat Politecnica de Valencia project 'Material Requirement Planning Fourth Generation (MRPIV) (Ref. PAID-05-12)'. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation Spanish Ministry of Science and Technology [DPI2010-19977] es_ES
dc.relation Universitat Politecnica de Valencia [PAID-05-12] es_ES
dc.relation.ispartof Applied Mathematical Modelling es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Fuzzy multi-objective integer linear programming es_ES
dc.subject Uncertainty modeling es_ES
dc.subject Supply chain planning es_ES
dc.subject Transport planning es_ES
dc.subject Procurement es_ES
dc.subject Automobile es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.apm.2014.04.053
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Centro de Investigación de Gestión e Ingeniería de la Producción - Centre d'Investigació de Gestió i Enginyeria de la Producció es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses es_ES
dc.description.bibliographicCitation Díaz-Madroñero Boluda, FM.; Peidro Payá, D.; Mula, J. (2014). A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain. Applied Mathematical Modelling. 38(23):5705-5725. doi:10.1016/j.apm.2014.04.053 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.apm.2014.04.053 es_ES
dc.description.upvformatpinicio 5705 es_ES
dc.description.upvformatpfin 5725 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 38 es_ES
dc.description.issue 23 es_ES
dc.relation.senia 269483
dc.identifier.eissn 1872-8480


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