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Managing inventory levels and time to market in assembly supply chains by swarm intelligence algorithms

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Computación Evolutiva y Redes Neuronales (EVANNAI)es
dc.contributor.authorMoncayo Martínez, Luis A.
dc.contributor.authorRamírez López, Adán
dc.contributor.authorRecio, Gustavo
dc.date.accessioned2020-09-21T11:53:11Z
dc.date.available2020-09-21T11:53:11Z
dc.date.issued2016-01-01
dc.description.abstractThe proposed work addresses the problem of placing safety stock under the guaranteed-service model when a set of supplying, manufacturing and delivery stages model the production system. Every stage has a set of options that can perform the stage and every option has an associated cost and time. Hence, the problem is to select an option per stage that minimises the safety stock and lead time at the same time. We proposed solving the problem using two swarm intelligent meta-heuristics, Ant Colony and Intelligent Water Drop, because of their results in solving NP-hard problems such as the safety stock problem. In our proposed algorithm, swarms are created and each one selects an option per stage with its safety stock and lead time. After that, the Pareto Optimality Criterion is applied to all the configurations to compute a Pareto front. A real-life logistic network of the automotive industry is solved using our proposed algorithm. Finally, we provided some multi-objective performance metrics to assess the performance of our approach and carried out a statistical analysis to support our conclusions.en
dc.description.sponsorshipAsociación Mexicana Cultura, A.C. As part of the National Research Network “Sistemas de Transporte y Logística”, the authors acknowledge all the support provided by the National Council of Science and Technology of Mexico (CONACYT) through the research program “Redes Temáticas de Investigación”en
dc.identifier.bibliographicCitationMoncayo–Martínez, L.A., Ramírez–López, A. & Recio, G. Managing inventory levels and time to market in assembly supply chains by swarm intelligence algorithms. Int J Adv Manuf Technol 82, 419–433 (2016)en
dc.identifier.doihttps://doi.org/10.1007/s00170-015-7313-x
dc.identifier.issn0268-3768
dc.identifier.publicationfirstpage419
dc.identifier.publicationissue1-4
dc.identifier.publicationlastpage433
dc.identifier.publicationtitleINTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGYen
dc.identifier.publicationvolume82
dc.identifier.urihttps://hdl.handle.net/10016/30839
dc.identifier.uxxiAR/0000017632
dc.language.isoengen
dc.publisherSpringer Natureen
dc.rightsCopyright © 2015, Springer Naturees
dc.rights.accessRightsopen accesses
dc.subject.ecienciaInformáticaes
dc.subject.otherSafety stocken
dc.subject.otherSwarm intelligenten
dc.subject.otherAutomotive industryen
dc.titleManaging inventory levels and time to market in assembly supply chains by swarm intelligence algorithmsen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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