Commenced in January 2007
Paper Count: 30982
A Multi-Objective Model for Supply Chain Network Design under Stochastic Demand
Abstract:In this article, the design of a Supply Chain Network (SCN) consisting of several suppliers, production plants, distribution centers and retailers, is considered. Demands of retailers are considered stochastic parameters, so we generate amounts of data via simulation to extract a few demand scenarios. Then a mixed integer two-stage programming model is developed to optimize simultaneously two objectives: (1) minimization the fixed and variable cost, (2) maximization the service level. A weighting method is utilized to solve this two objective problem and a numerical example is made to show the performance of the model.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1080926Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2006
 A. Alonso-Ayuso, L.F. Escudero, A. Garin, M.T. Ortuno, G. Perez, An approach for strategic supply chain planning under uncertainty based on stochastic 0-1 programming, J. Global Optim. 26 (2002) 97-124.
 A. Azaron, K.N. Brown, S.A. Tarim, M. Modarres, A multi-objective stochastic programming approach for supply chain design considering risk, Int. J. Production Economics 116 (2008) 129-138.
 Chopra, S., Meindl, P., 2004. Supply Chain Management: Strategy, Planning and Operation. Prentice Hall, Upper Saddle River, USA.
 C.J. Vidal, M. Goetschalckx, Modeling the effect of uncertainties on global logistics systems, J. Bus. Logist. 21 (1) (2000) 95-120.
 C. Vidal, M. Goetschalckx, Strategic production-distribution models: a critical review with emphasis on global supply chain models, Eur. J. Oper. Res. 98 (1997) 1-18.
 E.H. Sabri, B.M. Beamon, A multi-objective approach to simultaneous strategic and operational planning in supply chain design, Omega 28 (2000) 581-598.
 F. Altiparmak, M. Gen, L. Lin, T. Paksoy, 2006, A genetic algorithm approach for multi- objective optimization of supply chain Networks, Computers and Industrial Engineering 51, pp. 197-216.
 F.V. Louveaux, D. Peeters, A dual-based procedure for stochastic facility location, Oper. Res. 40 (1992) 564-573.
 G.J. Gutierrez, P. Kouvelis, A.A. Kurawala, A robustness approach to uncapacitated network design problems, Eur. J. Oper. Res. 94 (1996) 362-376.
 H. M. Bidhandi, R. Mohd. Yusuff, M. M. H. M. Ahmad, M. R. A. Bakar, Development of a new approach for deterministic supply chain network design, European Journal of Operational Research 198 (2009) 121-128.
 J. Xu, Q. Liuand R. Wang, A class of multi-objective supply chain networks optimal model under random fuzzy environment and its application to the industry of Chinese liquor, Information Sciences, Volume 178, Issue 8, 15 April 2008, Pages 2022-2043.
 M. Goh, J.I.S. Lim, F. Meng, A stochastic model for risk management in global supply chain networks, Eur. J. Oper. Res. 182 (2007) 164-173.
 P. Sch├╝tz, L. Stougie, A. Tomasgard, Stochastic facility location with general long-run costs and convex short-run costs, Computers & Operations Research, (2008) 2988-3000.
 P. Tsiakis, N. Shah, C.C. Pantelides, Design of multi echelon supply chain networks under demand uncertainty, Ind. Eng. Chem. Res. 40 (2001) 3585-3604.
 R.K.-M. Cheung, W.B. Powell, Models and algorithms for distribution problems with uncertain demands, Transport. Sci. 30 (1996) 43-59.
 S.A. MirHassani, C. Lucas, G. Mitra, E. Messina, C.A. Poojari, Computational solution of capacity planning models under uncertainty, Parallel Comput. 26(2000) 511-538.
 Sh. Rezapour , R. ZanjiraniFarahani, Strategic design of competing centralized supply chain networks for markets with deterministic demands, Advances in Engineering Software 41 (2010) 810-822.
 Snyder, L.V., 2006. Facility location under uncertainty: a review. IIE Transactions 38 (7), 537-554.
 T. Santoso, S. Ahmed, M. Goetschalckx, A. Shapiro, A stochastic programming approach for supply chain network design under uncertainty, Eur. J. Oper. Res. 167 (2005) 96-115.
 Van Landeghem, H., Vanmaele, H., 2002. Robust planning: a new paradigm for demand chain planning. Journal of Operation Management 20 (6), 769-783.
 W. Klibi, A. Martel, A. Guitouni, The design of robust value-creating supply chain networks: a critical review, Eur. J. Oper. Res. 203 (2) (2010) 283-293.
 Yu, C.-S., Li, H.-L., 2000. A robust optimization model for stochastic logistic problems. International Journal of Production Economics 64 (1- 3), 385-397.