Mostrar el registro sencillo del ítem
dc.contributor.author | Campuzano Bolarín, Francisco | es_ES |
dc.contributor.author | Mula, Josefa | es_ES |
dc.contributor.author | Peidro Payá, David | es_ES |
dc.date.accessioned | 2014-05-23T09:37:54Z | |
dc.date.issued | 2013-03-08 | |
dc.identifier.issn | 0020-7543 | |
dc.identifier.uri | http://hdl.handle.net/10251/37704 | |
dc.description.abstract | Campuzano, Mula, and Peidro (Fuzzy estimations and system dynamics for improving supply chains. Fuzzy Sets and Systems 161: 15301542) evaluate the behaviour of fuzzy estimations of demand instead of exponential smoothing for demand forecasts in a two-level (manufacturer and end customer) supply chain and demonstrate how the bullwhip effect and the amplification of inventory variance (NSAmp) can be effectively reduced. In this note, we extend and test the previous model to a three-level supply chain which consists of an end consumer, a retailer and a manufacturer. Here, the model is tested by using both Gaussian and autoregressive demand patterns. We show that the bullwhip effect and NSAmp also reduce at the level where fuzzy orders exist with good fill rate values. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Taylor & Francis: STM, Behavioural Science and Public Health Titles | es_ES |
dc.relation.ispartof | International Journal of Production Research | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Supply chain dynamics | es_ES |
dc.subject | Simulation | es_ES |
dc.subject | Fuzzy methods | es_ES |
dc.subject | Bullwhip effect | es_ES |
dc.subject.classification | ORGANIZACION DE EMPRESAS | es_ES |
dc.title | An extension to fuzzy estimations and system dynamics for improving supply chains | es_ES |
dc.type | Artículo | es_ES |
dc.embargo.lift | 10000-01-01 | |
dc.embargo.terms | forever | es_ES |
dc.identifier.doi | 10.1080/00207543.2012.760854 | |
dc.rights.accessRights | Cerrado | 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 | Campuzano Bolarín, F.; Mula, J.; Peidro Payá, D. (2013). An extension to fuzzy estimations and system dynamics for improving supply chains. International Journal of Production Research. 51(10):3156-3166. doi:10.1080/00207543.2012.760854 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://www.tandfonline.com/doi/abs/10.1080/00207543.2012.760854#.U3s84HZaZL0 | es_ES |
dc.description.upvformatpinicio | 3156 | es_ES |
dc.description.upvformatpfin | 3166 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 51 | es_ES |
dc.description.issue | 10 | es_ES |
dc.relation.senia | 253292 | |
dc.description.references | Balan, S., Vrat, P., & Kumar, P. (2007). Reducing the Bullwhip effect in a supply chain with fuzzy logic approach. International Journal of Integrated Supply Management, 3(3), 261. doi:10.1504/ijism.2007.012630 | es_ES |
dc.description.references | Balan, S., Vrat, P., & Kumar, P. (2009). RETRACTED: Information distortion in a supply chain and its mitigation using soft computing approach. Omega, 37(2), 282-299. doi:10.1016/j.omega.2007.01.004 | es_ES |
dc.description.references | Campuzano, F., Mula, J., & Peidro, D. (2010). Fuzzy estimations and system dynamics for improving supply chains. Fuzzy Sets and Systems, 161(11), 1530-1542. doi:10.1016/j.fss.2009.12.002 | es_ES |
dc.description.references | Cannella, S., & Ciancimino, E. (2009). On the Bullwhip Avoidance Phase: supply chain collaboration and order smoothing. International Journal of Production Research, 48(22), 6739-6776. doi:10.1080/00207540903252308 | es_ES |
dc.description.references | Cannella, S., A. P. Povoa, J. M. Framiñan and S. Relvas. 2013. “Metrics for bullwhip effect analysis.”Journal of the Operational Research Society64 (1): 1–16. | es_ES |
dc.description.references | Fransoo, J. C., & Wouters, M. J. F. (2000). Measuring the bullwhip effect in the supply chain. Supply Chain Management: An International Journal, 5(2), 78-89. doi:10.1108/13598540010319993 | es_ES |
dc.description.references | Kristianto, Y., Helo, P., Jiao, J. (Roger), & Sandhu, M. (2012). Adaptive fuzzy vendor managed inventory control for mitigating the Bullwhip effect in supply chains. European Journal of Operational Research, 216(2), 346-355. doi:10.1016/j.ejor.2011.07.051 | es_ES |
dc.description.references | Wangphanich, P., Kara, S., & Kayis, B. (2009). Analysis of the bullwhip effect in multi-product, multi-stage supply chain systems–a simulation approach. International Journal of Production Research, 48(15), 4501-4517. doi:10.1080/00207540902950852 | es_ES |
dc.description.references | Xiong, G., & Helo†, P. (2006). An application of cost-effective fuzzy inventory controller to counteract demand fluctuation caused by bullwhip effect. International Journal of Production Research, 44(24), 5261-5277. doi:10.1080/00207540600600114 | es_ES |
dc.description.references | Zarandi, M. H. F., Pourakbar, M., & Turksen, I. B. (2008). A Fuzzy agent-based model for reduction of bullwhip effect in supply chain systems. Expert Systems with Applications, 34(3), 1680-1691. doi:10.1016/j.eswa.2007.01.031 | es_ES |