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A capacitated lot-sizing model with sequence-dependent setups, parallel machines and bi-part injection moulding

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A capacitated lot-sizing model with sequence-dependent setups, parallel machines and bi-part injection moulding

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dc.contributor.author Mula, Josefa es_ES
dc.contributor.author Díaz-Madroñero Boluda, Francisco Manuel es_ES
dc.contributor.author Andres, B. es_ES
dc.contributor.author Poler, R. es_ES
dc.contributor.author Sanchis, R. es_ES
dc.date.accessioned 2022-07-22T18:06:19Z
dc.date.available 2022-07-22T18:06:19Z
dc.date.issued 2021-12 es_ES
dc.identifier.issn 0307-904X es_ES
dc.identifier.uri http://hdl.handle.net/10251/184694
dc.description.abstract [EN] This paper aims to propose a model for solving a capacitated lot-sizing problem with sequence-dependent setups (CLSD) and parallel machines in a bi-part injection moulding (BPIM) context that consists of injecting two different parts or products into the same mould in separate injection cavities. These two parts require the same sequence order and available capacity at the same instant, but generate different part inventories. The addressed problem should be considered a multi-machine CLSD-BPIM one. We provide a mixed integer linear programming (MILP) model for it. The proposed model is based on a real-world case study from a second-tier supplier of the automotive sector. In sequence setup, inventory and resource setup costs terms, the benefits of the proposed multi-machine CLSD-BPIM model are validated by comparing it with a single-machine CLSD-BPIM model that replicates the current planning scenario carried out in the company under study. Additionally, random instances based on the real problem have been generated and tested. The computational results exhibit optimal solutions for the small instances with an average of 0.2-second solution time, the medium instances present average gaps of 0.47% with 2.6 h and large instances present average gaps of 4% with 6 h solution time. es_ES
dc.description.sponsorship The research leading to these results was supported in part by the European Commission under the Grant Agreement No. 825631 `Zero Defects Manufacturing Platform' (ZDMP) (www.zdmp.eu); and the Spanish Ministry of Science, Innovation and Universities project entitled `Optimisation of zero-defects production technologies enabling supply chains 4.0 (CADS4.0)' (RTI2018-101344-B-I00). es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Applied Mathematical Modelling es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Capacitated lot-sizing es_ES
dc.subject Sequence-dependent setup times es_ES
dc.subject Injection moulding es_ES
dc.subject Parallel machines es_ES
dc.subject Mixed integer linear programming es_ES
dc.subject Automotive industry es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title A capacitated lot-sizing model with sequence-dependent setups, parallel machines and bi-part injection moulding es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.apm.2021.07.028 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-101344-B-I00/ES/OPTIMIZACION DE TECNOLOGIAS DE PRODUCCION CERO-DEFECTOS HABILITADORAS PARA CADENAS DE SUMINISTRO 4.0/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//RTI2018-101344-B-I00//OPTIMIZACION DE TECNOLOGIAS DE PRODUCCION CERO-DEFECTOS HABILITADORAS PARA CADENAS DE SUMINISTRO 4.0/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/636909/EU es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/825631/EU es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses es_ES
dc.description.bibliographicCitation Mula, J.; Díaz-Madroñero Boluda, FM.; Andres, B.; Poler, R.; Sanchis, R. (2021). A capacitated lot-sizing model with sequence-dependent setups, parallel machines and bi-part injection moulding. Applied Mathematical Modelling. 100:805-820. https://doi.org/10.1016/j.apm.2021.07.028 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.apm.2021.07.028 es_ES
dc.description.upvformatpinicio 805 es_ES
dc.description.upvformatpfin 820 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 100 es_ES
dc.relation.pasarela S\444069 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder COMISION DE LAS COMUNIDADES EUROPEA es_ES
dc.subject.ods 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación es_ES


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