Ir al menú de navegación principal Ir al contenido principal Ir al pie de página del sitio

Vol. 26 Núm. 44 (2017)

Articulos

Supply chain optimization with variable demand by considering financial criteria and scenarios

https://doi.org/10.19053/01211129.v26.n44.2017.5769

Publicado 2017-01-25

  • John Willmer Escobar

John Willmer Escobar
Ph. D. Universidad del Valle (Cali-Valle, Colombia).

Resumen

This paper contemplates the supply chain design problem of a large-scale company by considering the maximization of the Net Present Value. In particular, the variability of the demand for each type of product at each customer zone has been estimated. As starting point, this paper considers an established supply chain for which the main problem is to determine the decisions regarding expansion of distribution centers. The problem is solved by using a mixed-integer linear programming model, which optimizes the different demand scenarios. The proposed methodology uses a scheme of optimization based on the generation of multiple demand scenarios of the supply network. The model is based on a real case taken from a multinational food company, which supplies to the Colombian and some international markets. The obtained results were compared with the equivalent present costs minimization scheme of the supply network, and showed the importance and efficiency of the proposed approach as an alternative for the supply chain design with stochastic parameters.

Palabras clave

analysis of scenarios, logistics, Net Present Value (NPV), supply chain design, variability of the demand

PDF (English) XML (English)

Citas

  1. J. W. Escobar, “Rediseño de una red de distribución con variabilidad de demanda usando la metodología de escenarios,” Rev. Fac. Ing., vol. 21 (32), pp. 9-19, 2012. DOI: http://doi.org/10.19053/01211129.1439.
  2. A. Rostami, A. A. Anvary Rostami, S. Jalali, and A. R. Nazemi, “Relation between supply chain efficiency and supply chain finance,” International Research Journal of Applied and Basic Sciences, vol. 4 (2), pp. 416-423, 2013.
  3. P. Tsiakis, N. Shah, and C. C. Pantelides, “Design of Multi-echelon Supply Chain Networks under Demand Uncertainty,” Industrial & Engineering Chemistry Research, vol. 40 (16), pp. 3585-3604, Aug. 2001. DOI: http://doi.org/10.1021/ie0100030. DOI: https://doi.org/10.1021/ie0100030
  4. J. W. Escobar, “Modelación y optimización de redes de distribución de productos de consumo masivo con elementos estocásticos,” Proceedings of XIV Latin American Summer Workshop on Operations Research (ELAVIO), El Fuerte, México, 2009.
  5. J. W. Escobar, J. J. Bravo, and C. J. Vidal, “Optimización de redes de distribución de productos de consumo masivo en condiciones de riesgo,” Proceedings of XXXIII Congreso Nacional de Estadística e Investigación Operativa (SEIO), Madrid, Spain. May. 2012.
  6. J. W. Escobar, J. J. Bravo, and C. J. Vidal, “Optimización de una red de distribución con parámetros estocásticos usando la metodología de aproximación por promedios muéstrales,” Ingeniería y Desarrollo, vol. 31 (1), pp. 135-160, 2013.
  7. I. Mafla and J. W. Escobar, “Rediseño de una red de distribución para un grupo de empresas que pertenecen a un holding multinacional considerando variabilidad de la demanda,” Revista de la Facultad de Ingeniería U.C.V., vol. 30 (1), pp. 37-48, 2015.
  8. J. Ridlehoover, “Applying Monte Carlo Simulation and Risk Analysis to the Facility Location Problem,” The Engineering Economist, vol. 49 (3), pp. 237-252, Jan. 2004. DOI: http://doi.org/10.1080/00137910490498942. DOI: https://doi.org/10.1080/00137910490498942
  9. J. M. Laínez-Aguirre and L. Puigjaner, “Financial Issues in the Design of Supply Chains,” Proceedings of Advances in Integrated and Sustainable Supply Chain Planning, pp. 31-72. Springer International Publishing, 2015. DOI: https://doi.org/10.1007/978-3-319-10220-7_2
  10. A. Azaron, K. N. Brown, S. A. Tarim, and M. Modarres, “A multi-objective stochastic programming approach for supply chain design considering risk,” International Journal of Production Economics, vol. 116 (1), pp. 129-138, Nov. 2008. DOI: http://doi.org/10.1016/j.ijpe.2008.08.002. DOI: https://doi.org/10.1016/j.ijpe.2008.08.002
  11. I. Heckmann, T. Comes, and S. Nickel, “A critical review on supply chain risk–Definition, measure and modeling,” Omega, vol. 52, pp. 119-132, Apr. 2015. DOI: http://doi.org/10.1016/j.omega.2014.10.004. DOI: https://doi.org/10.1016/j.omega.2014.10.004
  12. P. Singhal, G. Agarwal, and M. L. Mittal, “Supply chain risk management: review, classification and future research directions,” International Journal of Business Science and Applied Management, vol. 6 (3), pp. 15-42, 2011. DOI: https://doi.org/10.4018/978-1-60960-135-5.ch002
  13. W. Klibi, A. Martel, and A. Guitouni, “The design of robust value-creating supply chain networks: a critical review,” European Journal of Operational Research, vol. 203 (2), pp. 283-293, Jun. 2010. DOI: http://doi.org/10.1016/j.ejor.2009.06.011. DOI: https://doi.org/10.1016/j.ejor.2009.06.011
  14. F. You and I. E. Grossmann, “Design of responsive supply chains under demand uncertainty,” Computers & Chemical Engineering, vol. 32 (12), pp. 3090-3111, Dec. 2008. DOI: http://doi.org/10.1016/j.compchemeng.2008.05.004. DOI: https://doi.org/10.1016/j.compchemeng.2008.05.004
  15. E. Huang and M. Goetschalckx, “Strategic robust supply chain design based on the Pareto-optimal tradeoff between efficiency and risk,” European Journal of Operational Research, vol. 237 (2), pp. 508-518, Sep. 2014. DOI: http://doi.org/10.1016/j.ejor.2014.02.038. DOI: https://doi.org/10.1016/j.ejor.2014.02.038
  16. M. Dal-Mas, S. Giarola, A. Zamboni, and F. Bezzo, “Strategic design and investment capacity planning of the ethanol supply chain under price uncertainty,” Biomass and bioenergy, vol. 35 (5), pp. 2059-2071, May. 2011. DOI: http://doi.org/10.1016/j.biombioe.2011.01.060. DOI: https://doi.org/10.1016/j.biombioe.2011.01.060
  17. J. Kim, Y. Lee, and I. Moon, “Optimization of a hydrogen supply chain under demand uncertainty,” International Journal of Hydrogen Energy, vol. 33 (18), pp. 4715-4729, Sep. 2008. DOI: http://doi.org/10.1016/j.ijhydene.2008.06.007. DOI: https://doi.org/10.1016/j.ijhydene.2008.06.007
  18. J. H. Vanston, W. Parker Frisbie, S. Cook Lopreato, and D. L. Boston Jr., “Alternate scenario planning,” Technological Forecasting and Social Change, vol. 10 (2), pp.159-180, Jan. 1977. DOI: http://doi.org/10.1016/0040-1625(77)90043-9. DOI: https://doi.org/10.1016/0040-1625(77)90043-9
  19. L. F. Escudero, P. V. Kamesam, A. J. King, and R. J.-B. Wets, “Production planning via scenario modelling,” Annals of Operations Research, vol. 43 (6), pp. 309-335, Jun. 1993. DOI: http://doi.org/10.1007/BF02025089. DOI: https://doi.org/10.1007/BF02025089
  20. L. F. Escudero and P. V. Kamesam. “On solving stochastic production planning problems via scenario modelling,” Top 3, vol. 1 (1), pp. 69-95, Jun. 1995. DOI: http://doi.org/10.1007/BF02574804. DOI: https://doi.org/10.1007/BF02574804
  21. D. Serra and V. Marianov, “The P-median Problem in a Changing Network: The Case of Barcelona,” Location Science, vol. 6 (1-4), pp. 383-394, May. 1998. DOI: http://doi.org/10.1016/S0966-8349(98)00049-7. DOI: https://doi.org/10.1016/S0966-8349(98)00049-7
  22. F. C. Lario, A. Rodriguez Villalobos, J. P. Garcia Sabater, and L. F. Escudero, “Análisis y definición de escenarios en programación estocástica para la gestión de la cadena de suministros en el sector del automóvil,” Proceedings of IV Congreso de Ingeniería de Organización, Sevilla, 2001.
  23. G. Guillén, F. D. Mele, M. J. Bagajewicz, A. Espuña, and L. Puigjaner, “Multiobjective supply chain design under uncertainty,” Chemical Engineering Science, vol. 60 (6), pp. 1535-1553, Mar. 2005. DOI: http://doi.org/10.1016/j.ces.2004.10.023. DOI: https://doi.org/10.1016/j.ces.2004.10.023
  24. W. Klibi and A. Martel. “Scenario-based supply chain network risk modeling,” European Journal of Operational Research, vol. 223 (3), pp. 644-658, Dec. 2012. DOI: http://doi.org/10.1016/j.ejor.2012.06.027. DOI: https://doi.org/10.1016/j.ejor.2012.06.027
  25. P. Longinidis and M.C. Georgidis, “Integration of financial statement analysis in the optimal design of supply chain networks under demand uncertainty,” International Journal of Production Economics, vol. 129 (2), pp. 262-276, Feb. 2011. DOI: http://doi.org/10.1016/j.ijpe.2010.10.018. DOI: https://doi.org/10.1016/j.ijpe.2010.10.018
  26. C. Hsu and H. Li, “Reliability evaluation and adjustment of supply chain network design with demand fluctuations,” International Journal of Production Economics, vol. 132 (1), pp. 131-145, Jul. 2011. DOI: http://doi.org/10.1016/j.ijpe.2011.03.020. DOI: https://doi.org/10.1016/j.ijpe.2011.03.020
  27. M. H. Carrillo Ramírez, G. R. Fiorillo Obando, and R. G. García Cáceres, “Modelo analítico para el estudio de una cadena de abastecimiento,” Ingeniería y Universidad, vol. 6 (2), pp.119-36, 2002.
  28. R. G. García-Cáceres, F. Palacios Gómez, and M. E. Martínez Avella, “Tactical planning of domestic supply chains,” Revista Facultad de Ingeniería Universidad de Antioquia, vol. 60, pp. 102-117, 2011.
  29. J. A. Rice, Mathematical Statistics and Data Analysis. Duxbury Press, 1995.
  30. J. W. Escobar and R. Linfati, “Un algoritmo metaheurístico basado en recocido simulado con espacio de búsqueda granular para el problema de localización y ruteo con restricciones de capacidad,” Revista Ingenierías Universidad de Medellín, vol. 11 (21), pp. 139-150, 2012.
  31. R. Bolaños, M. Granada, and J. W. Escobar, “A multiobjective non-dominated sorting genetic algorithm (NSGA-II) for the Multiple Traveling Salesman Problem,” Decision Science Letters, vol. 4 (4), pp. 559-568, 2015. DOI: http://doi.org/10.5267/j.dsl.2015.5.003. DOI: https://doi.org/10.5267/j.dsl.2015.5.003
  32. J. W. Escobar, “A hybrid metaheuristic algorithm for the capacitated location routing problem,” Dyna, vol. 82 (189), pp. 243-251, Feb. 2015. DOI: http://doi.org/10.15446/dyna.v82n189.48552. DOI: https://doi.org/10.15446/dyna.v82n189.48552
  33. J. W. Escobar, “Heuristic algorithms for the capacitated location-routing problem and the multi-depot vehicle routing problem,”. 4OR, vol. 12 (1), p. 99, 2014. DOI: https://doi.org/10.1007/s10288-013-0241-4

Descargas

Los datos de descargas todavía no están disponibles.

Artículos más leídos del mismo autor/a

Artículos similares

1 2 > >> 

También puede {advancedSearchLink} para este artículo.