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Master production schedule using robust optimization approaches in an automobile second-tier supplier

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Master production schedule using robust optimization approaches in an automobile second-tier supplier

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dc.contributor.author Martín, Antonio G. es_ES
dc.contributor.author Díaz-Madroñero Boluda, Francisco Manuel es_ES
dc.contributor.author Mula, Josefa es_ES
dc.date.accessioned 2021-05-20T03:33:05Z
dc.date.available 2021-05-20T03:33:05Z
dc.date.issued 2020-03 es_ES
dc.identifier.issn 1435-246X es_ES
dc.identifier.uri http://hdl.handle.net/10251/166522
dc.description.abstract [EN] This paper considers a real-world automobile second-tier supplier that manufactures decorative surface finishings of injected parts provided by several suppliers, and which devises its master production schedule by a manual spreadsheet-based procedure. The imprecise production time in this manufacturer's production process is incorporated into a deterministic mathematical programming model to address this problem by two robust optimization approaches. The proposed model and the corresponding robust solution methodology improve production plans by optimizing the production, inventory and backlogging costs, and demonstrate the their feasibility for a realistic master production schedule problem that outperforms the heuristic decision-making procedure currently being applied in the firm under study. es_ES
dc.description.sponsorship Funding was provided by Horizon 2020 Framework Programme (Grant Agreement No. 636909) in the frame of the "Cloud Collaborative Manufacturing Networks" (C2NET) project. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Central European Journal of Operations Research es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Robust optimization es_ES
dc.subject Master production schedule es_ES
dc.subject Uncertainty es_ES
dc.subject Automotive industry es_ES
dc.subject.classification ORGANIZACION DE EMPRESAS es_ES
dc.title Master production schedule using robust optimization approaches in an automobile second-tier supplier es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10100-019-00607-2 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/636909/EU/Cloud Collaborative Manufacturing Networks (C2NET)/ 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 Martín, AG.; Díaz-Madroñero Boluda, FM.; Mula, J. (2020). Master production schedule using robust optimization approaches in an automobile second-tier supplier. Central European Journal of Operations Research. 28(1):143-166. https://doi.org/10.1007/s10100-019-00607-2 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s10100-019-00607-2 es_ES
dc.description.upvformatpinicio 143 es_ES
dc.description.upvformatpfin 166 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 28 es_ES
dc.description.issue 1 es_ES
dc.relation.pasarela S\375645 es_ES
dc.contributor.funder European Commission es_ES
dc.description.references Alem DJ, Morabito R (2012) Production planning in furniture settings via robust optimization. Comput Oper Res 39:139–150. https://doi.org/10.1016/j.cor.2011.02.022 es_ES
dc.description.references Aloulou MA, Dolgui A, Kovalyov MY (2014) A bibliography of non-deterministic lot-sizing models. Int J Prod Res 52:2293–2310. https://doi.org/10.1080/00207543.2013.855336 es_ES
dc.description.references As’ad R, Demirli K, Goyal SK (2015) Coping with uncertainties in production planning through fuzzy mathematical programming: application to steel rolling industry. Int J Oper Res 22:1–30. https://doi.org/10.1504/IJOR.2015.065937 es_ES
dc.description.references Atamturk A, Zhang M (2007) Two-stage robust network flow and design under demand uncertainty. Oper Res 55:662–673. https://doi.org/10.1287/opre.1070.0428 es_ES
dc.description.references Aytac B, Wu SD (2013) Characterization of demand for short life-cycle technology products. Ann Oper Res 203:255–277. https://doi.org/10.1007/s10479-010-0771-5 es_ES
dc.description.references Ben-Tal A, Nemirovski A (1998) Robust convex optimization. Math Oper Res 23:769–805. https://doi.org/10.1287/moor.23.4.769 es_ES
dc.description.references Ben-Tal A, Nemirovski A (2000) Robust solutions of linear programming problems contaminated with uncertain data. Math Program 88:411–424. https://doi.org/10.1007/PL00011380 es_ES
dc.description.references Bertsimas D, Sim M (2004) The price of robustness. Oper Res 52:35–53. https://doi.org/10.1287/opre.1030.0065 es_ES
dc.description.references Caulkins JJ, Morrison E, Weidemann T (2007) Spreadsheet errors and decision making: evidence from field interviews. J Organ End User Comput 19:1–23 es_ES
dc.description.references Childerhouse P, Towill DR (2002) Analysis of the factors affecting real-world value stream performance. Int J Prod Res 40:3499–3518. https://doi.org/10.1080/00207540210152885 es_ES
dc.description.references Chu SCK (1995) A mathematical programming approach towards optimized master production scheduling. Int J Prod Econ 38:269–279. https://doi.org/10.1016/0925-5273(95)00015-G es_ES
dc.description.references Conlon JR (1976) Is your master production schedule feasible? Prod Invent Manag 17:56–63 es_ES
dc.description.references De La Vega J, Munari P, Morabito R (2017) Robust optimization for the vehicle routing problem with multiple deliverymen. Cent Eur J Oper Res. https://doi.org/10.1007/s10100-017-0511-x es_ES
dc.description.references Díaz-Madroñero M, Mula J, Jiménez M (2014a) Fuzzy goal programming for material requirements planning under uncertainty and integrity conditions. Int J Prod Res 52:6971–6988. https://doi.org/10.1080/00207543.2014.920115 es_ES
dc.description.references Díaz-Madroñero M, Mula J, Peidro D (2014b) A review of discrete-time optimization models for tactical production planning. Int J Prod Res 52:5171–5205. https://doi.org/10.1080/00207543.2014.899721 es_ES
dc.description.references Díaz-Madroñero M, Peidro D, Mula J (2014c) A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain. Appl Math Model 38:5705–5725. https://doi.org/10.1016/j.apm.2014.04.053 es_ES
dc.description.references Dolgui A, Ben Ammar O, Hnaien F et al (2013) Supply planning and inventory control under lead time uncertainty: a review. Stud Inform Control 22:255–268 es_ES
dc.description.references Dzuranin AC, Slater RD (2014) Business risks all identified? If you’re using a spreadsheet, think again. J Corp Account Finance 25:25–30. https://doi.org/10.1002/jcaf.21936 es_ES
dc.description.references Englberger J, Herrmann F, Manitz M (2016) Two-stage stochastic master production scheduling under demand uncertainty in a rolling planning environment. Int J Prod Res 54:6192–6215. https://doi.org/10.1080/00207543.2016.1162917 es_ES
dc.description.references Gabrel V, Murat C, Thiele A (2014) Recent advances in robust optimization: an overview. Eur J Oper Res 235:471–483 es_ES
dc.description.references Gharakhani M, Taghipour T, Farahani KJ (2010) A robust multi-objective production planning. Int J Ind Eng Comput 1:73–78. https://doi.org/10.5267/j.ijiec.2010.01.007 es_ES
dc.description.references González JJ, Reeves GR (1983) Master production scheduling: a multiple-objective linear programming approach. Int J Prod Res 21:553–562. https://doi.org/10.1080/00207548308942390 es_ES
dc.description.references Gorissen BL, Yanıkoğlu İ, den Hertog D (2015) A practical guide to robust optimization. Omega 53:124–137. https://doi.org/10.1016/j.omega.2014.12.006 es_ES
dc.description.references Grubbstrom RW, Tang O (2000) An overview of input-output analysis applied to production-inventory systems. Econ Syst Res 12:3–25. https://doi.org/10.1080/095353100111254 es_ES
dc.description.references Grubbström RW, Bogataj M, Bogataj L (2010) Optimal lotsizing within MRP theory. Annu Rev Control 34:89–100. https://doi.org/10.1016/J.ARCONTROL.2010.02.004 es_ES
dc.description.references Haojie Y, Lixin M, Canrong Z (2017) Capacitated lot-sizing problem with one-way substitution: a robust optimization approach. In: In 2017 3rd international conference on information management (ICIM). Institute of Electrical and Electronics Engineers Inc., pp 159–163 es_ES
dc.description.references Kara G, Özmen A, Weber G-W (2017) Stability advances in robust portfolio optimization under parallelepiped uncertainty. Cent Eur J Oper Res. https://doi.org/10.1007/s10100-017-0508-5 es_ES
dc.description.references Kawas B, Laumanns M, Pratsini E (2013) A robust optimization approach to enhancing reliability in production planning under non-compliance risks. OR Spectr 35:835–865. https://doi.org/10.1007/s00291-013-0339-2 es_ES
dc.description.references Kimms A (1998) Stability measures for rolling schedules with applications to capacity expansion planning, master production scheduling, and lot sizing. Omega 26:355–366. https://doi.org/10.1016/S0305-0483(97)00056-X es_ES
dc.description.references Ko M, Tiwari A, Mehnen J (2010) A review of soft computing applications in supply chain management. Appl Soft Comput 10:661–674. https://doi.org/10.1016/j.asoc.2009.09.004 es_ES
dc.description.references Körpeolu E, Yaman H, Selim Aktürk M (2011) A multi-stage stochastic programming approach in master production scheduling. Eur J Oper Res 213:166–179. https://doi.org/10.1016/j.ejor.2011.02.032 es_ES
dc.description.references Kovačić D, Bogataj M (2013) Reverse logistics facility location using cyclical model of extended MRP theory. Cent Eur J Oper Res 21:41–57. https://doi.org/10.1007/s10100-012-0251-x es_ES
dc.description.references Kuchta D (2011) A concept of a robust solution of a multicriterial linear programming problem. Cent Eur J Oper Res 19:605–613. https://doi.org/10.1007/s10100-010-0150-y es_ES
dc.description.references Lage Junior M, Godinho Filho M (2017) Master disassembly scheduling in a remanufacturing system with stochastic routings. Cent Eur J Oper Res 25:123–138. https://doi.org/10.1007/s10100-015-0428-1 es_ES
dc.description.references Lee SM, Moore LJ (1974) Practical approach to production scheduling. Prod Invent Manag J 15:79–92 es_ES
dc.description.references Lehtimaki AK (1987) Approach for solving decision planning of master scheduling by utilizing theory of fuzzy sets. Int J Prod Res 25:1781–1793 es_ES
dc.description.references Li Z, Li Z (2015) Optimal robust optimization approximation for chance constrained optimization problem. Comput Chem Eng 74:89–99. https://doi.org/10.1016/j.compchemeng.2015.01.003 es_ES
dc.description.references Li Z, Ding R, Floudas CA (2011) A Comparative theoretical and computational study on robust counterpart optimization: I. Robust linear optimization and robust mixed integer linear optimization. Ind Eng Chem Res 50:10567–10603. https://doi.org/10.1021/ie200150p es_ES
dc.description.references Li Z, Tang Q, Floudas CA (2012) A comparative theoretical and computational study on robust counterpart optimization: II. Probabilistic guarantees on constraint satisfaction. Ind Eng Chem Res 51:6769–6788. https://doi.org/10.1021/ie201651s es_ES
dc.description.references Mula J, Poler R, Garcia-Sabater J, Lario F (2006a) Models for production planning under uncertainty: a review. Int J Prod Econ 103:271–285. https://doi.org/10.1016/j.ijpe.2005.09.001 es_ES
dc.description.references Mula J, Poler R, Garcia JP (2006b) MRP with flexible constraints: a fuzzy mathematical programming approach. Fuzzy Sets Syst 157:74–97. https://doi.org/10.1016/j.fss.2005.05.045 es_ES
dc.description.references Mula J, Poler R, Garcia-Sabater JP (2008) Capacity and material requirement planning modelling by comparing deterministic and fuzzy models. Int J Prod Res 46:5589–5606. https://doi.org/10.1080/00207540701413912 es_ES
dc.description.references Mulvey JM, Vanderbei RJ, Zenios SA (1995) Robust optimization of large-scale systems. Oper Res 43:264–281. https://doi.org/10.1287/opre.43.2.264 es_ES
dc.description.references Nannapaneni S, Mahadevan S (2014) Uncertainty quantification in performance evaluation of manufacturing processes. In: 2014 IEEE international conference on Big Data (Big Data). IEEE, pp 996–1005 es_ES
dc.description.references Ng TS, Fowler J (2007) Semiconductor production planning using robust optimization. In: 2007 IEEE international conference on industrial engineering and engineering management. IEEE, pp 1073–1077 es_ES
dc.description.references Peidro D, Mula J, Poler RR, Lario F-C (2009) Quantitative models for supply chain planning under uncertainty: a review. Int J Adv Manuf Technol 43:400–420. https://doi.org/10.1007/s00170-008-1715-y es_ES
dc.description.references Pochet Y, Wolsey LA (2006) Production planning by mixed integer programming. Springer, Berlin es_ES
dc.description.references Powell SG, Baker KR, Lawson B (2008) A critical review of the literature on spreadsheet errors. Decis Support Syst 46:128–138. https://doi.org/10.1016/j.dss.2008.06.001 es_ES
dc.description.references Rahmani D, Ramezanian R, Fattahi P, Heydari M (2013) A robust optimization model for multi-product two-stage capacitated production planning under uncertainty. Appl Math Model 37:8957–8971. https://doi.org/10.1016/j.apm.2013.04.016 es_ES
dc.description.references Sahinidis NV (2004) Optimization under uncertainty: state-of-the-art and opportunities. Comput Chem Eng 28:971–983. https://doi.org/10.1016/j.compchemeng.2003.09.017 es_ES
dc.description.references Sakhaii M, Tavakkoli-Moghaddam R, Bagheri M, Vatani B (2015) A robust optimization approach for an integrated dynamic cellular manufacturing system and production planning with unreliable machines. Appl Math Model 40:169–191. https://doi.org/10.1016/j.apm.2015.05.005 es_ES
dc.description.references Soyster AL (1973) Convex programming with set-inclusive constraints and applications to inexact linear programming. Oper Res 21:1154–1157. https://doi.org/10.1287/opre.21.5.1154 es_ES
dc.description.references Supriyanto I, Noche B (2011) Fuzzy multi-objective linear programming and simulation approach to the development of valid and realistic master production schedule. Logist J. https://doi.org/10.2195/lj_proc_supriyanto_de_201108_01 es_ES
dc.description.references Tavakkoli-Moghaddam R, Sakhaii M, Vatani B et al (2014) A robust model for a dynamic cellular manufacturing system with production planning. Int J Eng 27:587–598. https://doi.org/10.5829/idosi.ije.2014.27.04a.09 es_ES
dc.description.references Vargas V, Metters R (2011) A master production scheduling procedure for stochastic demand and rolling planning horizons. Int J Prod Econ 132:296–302. https://doi.org/10.1016/j.ijpe.2011.04.025 es_ES
dc.description.references Wang J, Shu Y-F (2005) Fuzzy decision modeling for supply chain management. Fuzzy Sets Syst 150:107–127 es_ES
dc.description.references Weng ZK, Parlar M (2005) Managing build-to-order short life-cycle products: benefits of pre-season price incentives with standardization. J Oper Manag 23:482–495. https://doi.org/10.1016/j.jom.2004.10.008 es_ES
dc.description.references Werner R (2008) Cascading: an adjusted exchange method for robust conic programming. Cent Eur J Oper Res 16:179–189. https://doi.org/10.1007/s10100-007-0047-6 es_ES
dc.description.references Yu C-S, Li H-L (2000) A robust optimization model for stochastic logistic problems. Int J Prod Econ 64:385–397. https://doi.org/10.1016/S0925-5273(99)00074-2 es_ES


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