A Multi-Objective Model for Supply Chain Network Design under Stochastic Demand
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.
[1] 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.
[2] 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.
[3] Chopra, S., Meindl, P., 2004. Supply Chain Management: Strategy,
Planning and Operation. Prentice Hall, Upper Saddle River, USA.
[4] C.J. Vidal, M. Goetschalckx, Modeling the effect of uncertainties on
global logistics systems, J. Bus. Logist. 21 (1) (2000) 95-120.
[5] 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.
[6] 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.
[7] 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.
[8] F.V. Louveaux, D. Peeters, A dual-based procedure for stochastic
facility location, Oper. Res. 40 (1992) 564-573.
[9] G.J. Gutierrez, P. Kouvelis, A.A. Kurawala, A robustness approach to
uncapacitated network design problems, Eur. J. Oper. Res. 94 (1996)
362-376.
[10] 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.
[11] 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.
[12] 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.
[13] 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.
[14] 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.
[15] R.K.-M. Cheung, W.B. Powell, Models and algorithms for distribution
problems with uncertain demands, Transport. Sci. 30 (1996) 43-59.
[16] 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.
[17] 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.
[18] Snyder, L.V., 2006. Facility location under uncertainty: a review. IIE
Transactions 38 (7), 537-554.
[19] 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.
[20] Van Landeghem, H., Vanmaele, H., 2002. Robust planning: a new
paradigm for demand chain planning. Journal of Operation Management
20 (6), 769-783.
[21] 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.
[22] 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.
[1] 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.
[2] 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.
[3] Chopra, S., Meindl, P., 2004. Supply Chain Management: Strategy,
Planning and Operation. Prentice Hall, Upper Saddle River, USA.
[4] C.J. Vidal, M. Goetschalckx, Modeling the effect of uncertainties on
global logistics systems, J. Bus. Logist. 21 (1) (2000) 95-120.
[5] 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.
[6] 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.
[7] 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.
[8] F.V. Louveaux, D. Peeters, A dual-based procedure for stochastic
facility location, Oper. Res. 40 (1992) 564-573.
[9] G.J. Gutierrez, P. Kouvelis, A.A. Kurawala, A robustness approach to
uncapacitated network design problems, Eur. J. Oper. Res. 94 (1996)
362-376.
[10] 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.
[11] 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.
[12] 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.
[13] 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.
[14] 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.
[15] R.K.-M. Cheung, W.B. Powell, Models and algorithms for distribution
problems with uncertain demands, Transport. Sci. 30 (1996) 43-59.
[16] 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.
[17] 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.
[18] Snyder, L.V., 2006. Facility location under uncertainty: a review. IIE
Transactions 38 (7), 537-554.
[19] 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.
[20] Van Landeghem, H., Vanmaele, H., 2002. Robust planning: a new
paradigm for demand chain planning. Journal of Operation Management
20 (6), 769-783.
[21] 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.
[22] 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.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:62353", author = "F. Alborzi and H. Vafaei and M.H. Gholami and M.M. S. Esfahani", title = "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.", keywords = "Mixed Integer Programming, Multi-objective
Optimization, Stochastic Demand, Supply Chain Design, Two Stage
Programming", volume = "5", number = "11", pages = "2489-5", }