Open Access Open Access  Restricted Access Subscription or Fee Access

Improvement in the Coupling of Procurement Process and Production Planning by Simulation Under Stochastic Demand and Lead Time

(*) Corresponding author

Authors' affiliations



Inventory control management is an essential matter in supply chain, which helps to maintain an optimum level of investment in the inventory. This requires a global optimization of a complex logistics and inventory system. In this paper, we present a simulation model characterizing the complex dynamic behavior of procurement system that takes into account the coupling with production planning, in the context of stochastic demand and delivery lead-time. We have carried out this model in order to fill up the existing researches, as this area of study has not been dealt with sufficiently in the literature. Moreover, this model was developed for multiple-supplier, multiproduct and convergent bill of materials, also we introduced two characteristics to model each type of decision, the anticipation period and the delay in obtaining. The outcomes of our simulator are in the form of several scenarios generated by simulation replications, these results proving the strength of the chosen approach.
Copyright © 2014 Praise Worthy Prize - All rights reserved.


Simulation Model; Inventory Control; Stochastic Demand and Delivery Lead Time; Procurement and Production Coupling; Simulation Scenarios

Full Text:



Arda, Y., Politiques d'approvisionnement dans les systèmes à plusieurs fournisseurs et Optimisation des décisions dans les chaînes logistiques décentralisées. Thèse de Doctorat, Institut National des Sciences Appliquées de Toulouse, 2008.

Banks J., Carson II J.S., Nelsson B.L., Nicol D.M.: Discrete-event System Simulation. Fourth Edition, Pearson Prentice Hall, New Jersey 2005.

Bell S.G.: Simulation: A Data-Driven Tool to Lower Costs ASCET. vol. 4, Montgomery Research, San Francisco 2002.

Camisullis, C. & Giard, V., A new need for safety stocks in a supply chain dedicated to customized mass production, Supply Chain Forum: An International Journal, 9, 88-96, 2008.

Chopra, S. & Meindl, P. Supply chain management – strategy, plan¬ning and operation. Englewood Cliffs: Prentice-Hall, 2001.

Dolgui et Al.. Configuration d'un système d'assemblage multi-niveaux sous incertitudes des délais d'approvisionnement. 9e Conférence Internationale de Modélisation, Optimisation et SIMulation - MOSIM'12 06 au 08 Juin 2012 - Bordeaux – France.

Douraid, A. Lissane Elhaq, S. and Ech-cheikh, H., "Conceptualisation et modélisation pour la simulation des chaînes logistiques d'approvisionnement," Congrès International de Génie Industriel et Management des Systèmes 2012.

Ech-Cheikh, H. Lissane Elhaq, S. and Douraid, A., Modélisation flexible de flux et du processus de pilotage d'un système de distribution multi-échelon. 10ème congrès international de génie industriel (CIGI) juin 2013.

Fallah-Jamshidi S., Karimi N., and Zandieh M., A hybrid multi-objective genetic algorithm for planning order release date in two level assembly system with random lead times. Expert Systems with Applications, 38(11), p. 13549-13554, 2011.

H.J. Zimmermann, Fuzzy Set Theory - and its Applications, 2nd Revised Edition, Kluwer Academic Publishers, Dordrecht, MA, 1991.

Galasso F., François J., Mahmoudi J., Proposition d'une grille de classification de la littérature en gestion de chaîne logistique (supply chain management), Actes du 6ème Congrès de Génie Industriel (CIGI2005), Besançon (France), 7-10 juin, 2005.

Lee, Padmanabhan & Whang, Lee, H. L., Padmanabhan, V., Whang, S. "The Bullwhip Effect in Supply Chain," Sloan Management Review, 38, 93-102, 1977.

Martins, P.T.; Laugeni, F. P. Administração da produção., São Paulo, SP: Editora Saraiva, 2002.

Sabri, E. H. Beamon, B. M., A multi-objective approach to simultaneous strategic and operational planning in supply chain design'. The International Journal of Management Science. 28: 581-598, 2000.

Stefanovic D., Stefanovic N., Radenkovic B.: Supply network modelling and simulation methodology. Simulation Modelling Practice and Theory 17 (2009), p. 743-766.

Tang O., and Grubbstrom R.W., The detailed coordination problem in a two-level assembly system with stochastic lead times. International Journal of Production Economics, 81-82, p. 415-429, 2003.

Thomas, D. Tyworth, J., "Pooling lead-time risk by splitting orders: A critical review," Transportation Research Part E, 42(4), 2006, 245-257.

Villeminot, A., Modélisation et simulation de la logistique d'approvisionnement dans l'industrie automobile : Application pour un grand constructeur. Thèse doctorat de l'université Henri Poincaré, Nancy-I, 2004.

W. David Kelton, Randall P. Sadowski, David T. Sturrock, Simulation with Arena Book., Page 3, edition 2006.

Benkachcha, S., Benhra, J., El Hassani, H., Demand forecasting in supply chain: Comparing multiple linear regression and artificial neural networks approaches, (2014) International Review on Modelling and Simulations (IREMOS), 7 (2), pp. 279-286.


  • There are currently no refbacks.

Please send any question about this web site to
Copyright © 2005-2022 Praise Worthy Prize