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dc.contributor.author | Grillo-Espinoza, Hanzel | es_ES |
dc.contributor.author | Alemany Díaz, María Del Mar | es_ES |
dc.contributor.author | Ortiz Bas, Ángel | es_ES |
dc.contributor.author | Mula, Josefa | es_ES |
dc.date.accessioned | 2019-09-05T20:04:33Z | |
dc.date.available | 2019-09-05T20:04:33Z | |
dc.date.issued | 2018 | es_ES |
dc.identifier.issn | 1562-2479 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/125105 | |
dc.description.abstract | [EN] In this paper, in order to reliably meet the homogeneity required by customers, a fuzzy model is proposed to support the promising process in LHP contexts after taking into account uncertainty in planned homoge- neous sublots. The fuzzy model is translated into an alpha- parametric equivalent crisp model. Here, it is important to highlight another important novelty of the paper related to the proposed methodology to analyse the suitability of the minimum degree of possibility (the a-cut), by an adapted TOPSIS-based fuzzy procedure. Finally, the experimental design, which is inspired in the ceramic sector, proves both the validity of the model and a better performance of the fuzzy model compared to the deterministic one, in several executions with forecasts of the real size of homogeneous sublots. | es_ES |
dc.description.sponsorship | This research is partly supported by: The Ministry of Science, Technology and Telecommunications of the of Costa Rica Government (MICITT), through the Programme of Innovation and Human Capital for Competitiveness (PINN)(Contract No. PED-019-2015-1); and the Spanish Ministry of Economy and Competitiveness Projects "Methods and models for operations planning and order management in supply chains characterised by uncertainty in production due to the lack of product uniformity'' (PLANGES-FHP) (Ref. DPI2011-23597) and "Operations design and Management of Global Supply Chains'' (GLOBOP) (Ref. DPI2012-38061-C02-01). | |
dc.language | Inglés | es_ES |
dc.publisher | Springer-Verlag | es_ES |
dc.relation.ispartof | International Journal of Fuzzy Systems | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Order promising | es_ES |
dc.subject | Lack of homogeneity in the product | es_ES |
dc.subject | Uncertainty | es_ES |
dc.subject | Interdependent fuzzy coefficients | es_ES |
dc.subject | Fuzzy TOPSIS | es_ES |
dc.subject | Ceramic sector | es_ES |
dc.subject.classification | ORGANIZACION DE EMPRESAS | es_ES |
dc.title | A Fuzzy Order Promising Model With Non-Uniform Finished Goods | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1007/s40815-017-0317-y | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//DPI2011-23597/ES/METODOS Y MODELOS PARA LA PLANIFICACION DE OPERACIONES Y GESTION DE PEDIDOS EN CADENAS DE SUMINISTRO CARACTERIZADAS POR LA FALTA DE HOMOGENEIDAD EN EL PRODUCTO/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//DPI2012-38061-C02-01/ES/DISEÑO Y GESTION DE OPERACIONES EN CADENAS GLOBALES DE SUMINISTRO/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICITT//PED-019-2015-1/ | |
dc.rights.accessRights | Cerrado | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses | es_ES |
dc.description.bibliographicCitation | Grillo-Espinoza, H.; Alemany Díaz, MDM.; Ortiz Bas, Á.; Mula, J. (2018). A Fuzzy Order Promising Model With Non-Uniform Finished Goods. International Journal of Fuzzy Systems. 20(1):187-208. https://doi.org/10.1007/s40815-017-0317-y | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://doi.org/10.1007/s40815-017-0317-y | es_ES |
dc.description.upvformatpinicio | 187 | es_ES |
dc.description.upvformatpfin | 208 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 20 | es_ES |
dc.description.issue | 1 | es_ES |
dc.relation.pasarela | S\341706 | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |
dc.contributor.funder | Ministerio de Ciencia Tecnología y Telecomunicaciones de Costa Rica | |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |
dc.description.references | Ahumada, O., Villalobos, J.R.: Operational model for planning the harvest and distribution of perishable agricultural products. Int. J. Prod. Econ. 133.2, 677–687 (2011). doi: 10.1016/j.ijpe.2011.05.015 | es_ES |
dc.description.references | Davoli, G. et al.: A stochastic simulation approach for production scheduling and investment planning in the tile industry. Int. J. Eng. Sci. Technol. 2(9) (2010). doi: 10.4314/ijest.v2i9.64006 . | es_ES |
dc.description.references | Grillo, H., Alemany, M.M.E., Ortiz, A.: A review of mathematical models for supporting the order promising process under Lack of Homogeneity in Product and other sources of uncertainty. Comput. Ind. Eng. 91, 239–261 (2016). doi: 10.1016/j.cie.2015.11.013 | es_ES |
dc.description.references | Alemany, M.M.E., et al.: Order promising process for extended collaborative selling chain. Prod. Plann. Control 19.2, 105–131 (2008). doi: 10.1080/09537280801896011 | es_ES |
dc.description.references | Alemany, M.M.E., et al.: A model driven decision support system for reallocation of supply to orders under uncertainty in ceramic companies. Technol. Econ. Dev. Econ. 21.4, 596–625 (2015). doi: 10.3846/20294913.2015.1055613 | es_ES |
dc.description.references | Alarcón, F., Alemany, M.M.E., Ortiz, A.: Conceptual framework for the characterization of the order promising process in a collaborative selling network context. Int. J. Prod. Econ. 120.1, 100–114 (2009). doi: 10.1016/j.ijpe.2008.07.031 | es_ES |
dc.description.references | Bui, T., Sebastian, H.-J.: IEEE. Integration of multi-criteria decision analysis and negotiation in order promising’. In: 43rd Hawaii International Conference on Systems Sciences vol 1–5. Proceedings of the Annual Hawaii International Conference on System Sciences. pp. 1115–1124 (2010). doi: 10.1109/HICSS.2010.237 | es_ES |
dc.description.references | Ball, M.O., Chen, C.-Y., Zhao, Z.-Y.: In: Simchi-Levi, D., Wu, S.D., Shen, Z.-J. (eds.) Handbook of Quantitative Supply Chain Analysis: Modeling in the E-Business Era”. Chap. Available to Promise, pp. 447–483. Springer, Boston (2004). doi: 10.1007/978-1-4020-7953-5_11 | es_ES |
dc.description.references | Alemany, M.M.E., et al.: Available-To-Promise modeling for multi-plant manufacturing characterized by lack of homogeneity in the product: An illustration of a ceramic case. Appl. Math. Model. 37.5, 3380–3398 (2013). doi: 10.1016/j.apm.2012.07.022 | es_ES |
dc.description.references | Jiménez, M., et al.: Linear programming with fuzzy parameters: an interactive method resolution. Eur. J. Oper. Res. 177.3, 1599–1609 (2007). doi: 10.1016/j.ejor.2005.10.002 | es_ES |
dc.description.references | Peidro, D., et al.: A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment. Eur. J. Oper. Res. 205.1, 65–80 (2010). doi: 10.1016/j.ejor.2009.11.031 | es_ES |
dc.description.references | Yong, D.: Plant location selection based on fuzzy TOPSIS. Int. J. Adv. Manuf. Technol. 28.7–8, 839–844 (2006). doi: 10.1007/s00170-004-2436-5 | es_ES |
dc.description.references | Chen, C.-T.: A fuzzy approach to select the location of the distribution center. In: Fuzzy Sets and Systems 118.1, pp. 65–73 (2001) | es_ES |
dc.description.references | Chen, C.-T.: Extensions of the TOPSIS for group decision-making under fuzzy environment. In: Fuzzy Sets and Systems 114.1, pp. 1–9 (2000). | es_ES |
dc.description.references | Wang, Y.-M., Elhag, T.M.: Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. In: Expert Systems with Applications 31.2, pp. 309–319 (2006) | es_ES |
dc.description.references | Wang, T.-C., Chang, T.-H.: Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. In: Expert Systems with Applications 33.4, pp. 870–880 (2007) | es_ES |
dc.description.references | Gupta, A., Maranas, C.D.: Managing demand uncertainty in supply chain planning. In: 2nd Pan American Workshop in Process Systems Engineering 27.8–9, pp. 1219–1227 (Sept. 2003). doi: 10.1016/S0098-1354(03)00048-6 | es_ES |
dc.description.references | Lababidi, H.M.S., et al.: Optimizing the supply chain of a petrochemical company under uncertain operating and economic conditions. Ind. Eng. Chem. Res. 43.1, 63–73 (2004). doi: 10.1021/ie030555d | es_ES |
dc.description.references | Santoso, T., et al.: A stochastic programming approach for supply chain network design under uncertainty. Eur. J. Oper. Res. 167.1, 96–115 (2005). doi: 10.1016/j.ejor.2004.01.046 | es_ES |
dc.description.references | Sodhi, M.S.: Managing demand risk in tactical supply chain planning for a global consumer electronics company. Prod. Oper. Manag. 14.1, 69–79 (2009). doi: 10.1111/j.1937-5956.2005.tb00010.x | es_ES |
dc.description.references | Mula, J., Peidro, D., Poler, R.: The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand. Integr. Global Supply Chain 128.1, 136–143 (2010). doi: 10.1016/j.ijpe.2010.06.007 | es_ES |
dc.description.references | Wang, J., Shu, Y.-F.: Fuzzy decision modeling for supply chain management. Fuzzy Sets Syst. 150.1, 107–127 (2005). doi: 10.1016/j.fss.2004.07.005 | es_ES |
dc.description.references | Bellman, R.E., Zadeh, L.A.: Decision-making in a fuzzy environment. In: Management Science 17.4 (Dec. 1970). doi: 10.1287/mnsc.17.4.B141 | es_ES |
dc.description.references | Dubois, D., Prade, H.: Possibility Theory: An Approach to Computerized Processing of Uncertainty. Springer Science & Business Media, New York (2012) | es_ES |
dc.description.references | Dubois, D., Fargier, H., Fortemps, P.: Fuzzy scheduling: modelling flexible constraints vs. coping with incomplete knowledge. Fuzzy Sets Sched. Plann. 147.2, 231–252 (2003). doi: 10.1016/S0377-2217(02)00558-1 | es_ES |
dc.description.references | Alemany, M.M.E., et al.: A fuzzy model for shortage planning under uncertainty due to lack of homogeneity in planned production lots. Appl. Math. Model. 39.15, 4463–4481 (2015). doi: 10.1016/j.apm.2014.12.057 | es_ES |
dc.description.references | Gen, M., Tsujimura, Y., Ida, K.: Method for solving multiobjective aggregate production planning problem with fuzzy parameters. Comput. Ind. Eng. 23.1–4, 117–120 (1992). doi: 10.1016/0360-8352(92)90077-W | es_ES |
dc.description.references | Peidro, D., Vasant, P.: Transportation planning with modified S-curve membership functions using an interactive fuzzy multi-objective approach. Appl. Soft Comput. 11.2, 2656–2663 (2011). doi: 10.1016/j.asoc.2010.10.014 | es_ES |
dc.description.references | Cadenas, J., Verdegay, J.: Using fuzzy numbers in linear programming. In: IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 27.6, pp. 1016–1022 (Dec. 1997). doi: 10.1109/3477.650062 | es_ES |
dc.description.references | Peidro, D., et al.: Fuzzy optimization for supply chain planning under supply, demand and process uncertainties. Fuzzy Sets Syst. 160.18, 2640–2657 (2009). doi: 10.1016/j.fss.2009.02.021 | es_ES |
dc.description.references | Chu, T.-C.: Facility location selection using fuzzy TOPSIS under group decisions. Int. J Uncertain. Fuzziness Knowledgebased Syst. 10.06, 687–701 (2002). doi: 10.1142/S0218488502001739 | es_ES |
dc.description.references | Chamodrakas, I., Alexopoulou, N., Martakos, D.: Customer evaluation for order acceptance using a novel class of fuzzy methods based on TOPSIS. Exp. Syst. Appl. 36.4, 7409–7415 (2009). doi: 10.1016/j.eswa.2008.09.050 | es_ES |
dc.description.references | Nakhaeinejad, M., Nahavandi, N.: An interactive algorithm for multiobjective flow shop scheduling with fuzzy processing time through resolution method and TOPSIS. Int. J. Adv. Manuf. Technol. 66.5–8, 1047–1064 (2013). doi: 10.1007/s00170-012-4388-5 | es_ES |
dc.description.references | Shekarian, E., et al.: A fuzzy reverse logistics inventory system integrating economic order/production quantity models. Int. J. Fuzzy Syst. 18.6, 1141–1161 (2016). doi: 10.1007/s40815-015-0129-x | es_ES |
dc.description.references | Büyüközkan, G., Parlak, I.B., Tolga, A.C.: Evaluation of knowledge management tools by using an interval type-2 fuzzy TOPSIS method. Int. J. Comput. Intell. Syst. 9.5, 812–826 (2016) | es_ES |
dc.description.references | Saradhi, B. Pardha., Shankar, N. R., Suryanarayana, C.: Novel distance measure in fuzzy TOPSIS for supply chain strategy based supplier selection. Math. Probl. Eng. 2016 (2016) | es_ES |
dc.description.references | Senvar, O., Turanoglu, E., Kahraman, C.: Usage of metaheuristics in engineering: a literature review. In: Meta–Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance, pp. 484–528 (2013). doi: 10.4018/978-1-4666-2086-5.ch016 | es_ES |
dc.description.references | Grillo, H., et al.: Application of particle swarm optimisation with backward calculation to solve a fuzzy multi-objective supply chain master planning model. Int. J. Bio-Inspired Comput. 7.3, 157–169 (2015). doi: 10.1504/IJBIC.2015.069557 | es_ES |
dc.description.references | Rajavel, R., Thangarathanam, M.: Adaptive probabilistic behavioural learning system for the effective behavioural decision in cloud trading negotiation market. Futur. Gener. Comput. Syst. 58, 29–41 (2016) | es_ES |