CLC number: TP393; F22
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2014-11-13
Cited: 1
Clicked: 7383
Citations: Bibtex RefMan EndNote GB/T7714
Mohammad Mohajer Tabrizi, Behrooz Karimi. Supply chain network design under uncertainty with new insights from contracts[J]. Journal of Zhejiang University Science C, 2014, 15(12): 1106-1122.
@article{title="Supply chain network design under uncertainty with new insights from contracts",
author="Mohammad Mohajer Tabrizi, Behrooz Karimi",
journal="Journal of Zhejiang University Science C",
volume="15",
number="12",
pages="1106-1122",
year="2014",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1300279"
}
%0 Journal Article
%T Supply chain network design under uncertainty with new insights from contracts
%A Mohammad Mohajer Tabrizi
%A Behrooz Karimi
%J Journal of Zhejiang University SCIENCE C
%V 15
%N 12
%P 1106-1122
%@ 1869-1951
%D 2014
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1300279
TY - JOUR
T1 - Supply chain network design under uncertainty with new insights from contracts
A1 - Mohammad Mohajer Tabrizi
A1 - Behrooz Karimi
J0 - Journal of Zhejiang University Science C
VL - 15
IS - 12
SP - 1106
EP - 1122
%@ 1869-1951
Y1 - 2014
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1300279
Abstract: suppliers, manufacturers, warehouses, and customers acting within a single period. The single owner of the manufacturing plants signs a contract with each of the suppliers to satisfy demand from downstream. Available contracts consist of long-term and option contracts, and unmet demand is satisfied by purchasing from the spot market. In this supply chain, customer demand, supplier capacity, plants and warehouses, transportation costs, and spot prices are uncertain. Two models are proposed here: a risk-neutral two-stage stochastic model and a risk-averse model that considers risk measures. A solution strategy based on sample average approximation is then proposed to handle large scale problems. Extensive computational studies prove the important role of contracts in the design process, especially a portfolio of contracts. For instance, we show that long-term contract alone has similar impacts to having no contracts, and that option contract alone gives inferior results to a combination of option and long-term contracts. We also show that the proposed solution methodology is able to obtain good quality solutions for large scale problems.
[1]Badri, H., Bashiri, M., Hejazi, T.H., 2013. Integrated strategic and tactical planning in a supply chain network design with a heuristic solution method. Comput. Oper. Res., 40(4):1143-1154.
[2]Correia, I., Melo, T., Saldanha-da-Gama, F., 2013. Comparing classical performance measures for a multi-period, two-echelon supply chain network design problem with sizing decisions. Comput. Ind. Eng., 64(1):366-380.
[3]Das, K., 2011. Integrating effective flexibility measures into a strategic supply chain planning model. Eur. J. Oper. Res., 211(1):170-183.
[4]Feng, Y., Martel, A., D’Amours, S., et al., 2013. Coordinated contract decisions in a make-to-order manufacturing supply chain: a stochastic programming approach. Prod. Oper. Manag., 22(3):642-660.
[5]Georgiadis, M.C., Tsiakis, P., Longinidis, P., et al., 2011. Optimal design of supply chain networks under uncertain transient demand variations. Omega, 39(3):254-272.
[6]Goetschalckx, M., Huang, E., Mital, P., 2013. Trading off supply chain risk and efficiency through supply chain design. Procedia Comput. Sci., 16:658-667.
[7]Goldratt, E.M., Fox, R.E., 1996. The Race. North River Press.
[8]Kamath, K.R., Pakkala, T.P.M., 2002. A Bayesian approach to a dynamic inventory model under an unknown demand distribution. Comput. Oper. Res., 29(4):403-422.
[9]Melo, M.T., Nickel, S., Saldanha-da-Gama, F., 2009. Facility location and supply chain management—a review. Eur. J. Oper. Res., 196(2):401-412.
[10]Nagurney, A., 2010. Optimal supply chain network design and redesign at minimal total cost and with demand satisfaction. Int. J. Prod. Econ., 128(1):200-208.
[11]Noyan, N., 2012. Risk-averse two-stage stochastic programming with an application to disaster management. Comput. Oper. Res., 39(3):541-559.
[12]Paksoy, T., Özceylan, E., Weber, G.W., 2013. Profit oriented supply chain network optimization. Cent. Eur. J. Oper. Res., 21(2):455-478.
[13]Pan, F., Nagi, R., 2010. Robust supply chain design under uncertain demand in agile manufacturing. Comput. Oper. Res., 37(4):668-683.
[14]Rajgopal, J., Wang, Z., Schaefer, A.J., et al., 2011. Integrated design and operation of remnant inventory supply chains under uncertainty. Eur. J. Oper. Res., 214(2):358-364.
[15]Rockafellar, R.T., Uryasev, S., 2000. Optimization of conditional value-at-risk. J. Risk, 2(3):21-42.
[16]Santoso, T., 2003. A Comprehensive Model and Efficient Solution Algorithm for the Design of Global Supply Chains Under Uncertainty. PhD Thesis, Georgia Institute of Technology, USA.
[17]Santoso, T., Ahmed, S., Goetschalckx, M., et al., 2005. A stochastic programming approach for supply chain network design under uncertainty. Eur. J. Oper. Res., 167(1):96-115.
[18]Shapiro, A., Homem-de-Mello, T., 1998. A simulation-based approach to two-stage stochastic programming with recourse. Math. Program., 81(3):301-325.
[19]Simchi-Levi, D., Kaminsky, P., Simchi-Levi, E., 2007. Designing and Managing the Supply Chain: Concepts, Strategies, and Case Studies (3rd Ed.). McGraw-Hill International Edition, USA.
[20]Tabrizi, B.H., Razmi, J., 2013. Introducing a mixed-integer non-linear fuzzy model for risk management in designing supply chain networks. J. Manuf. Syst., 32(2):295-307.
[21]Thanh, P.N., Péton, O., Bostel, N., 2010. A linear relaxation-based heuristic approach for logistics network design. Comput. Ind. Eng., 59(4):964-975.
[22]Tiwari, M.K., Raghavendra, N., Agrawal, S., et al., 2010. A hybrid taguchi-immune approach to optimize an integrated supply chain design problem with multiple shipping. Eur. J. Oper. Res., 203(1):95-106.
[23]Wang, W., 2007. Sample Average Approximation of Risk-Averse Stochastic Programs. PhD Thesis, Georgia Institute of Technology, USA.
[24]Wever, M., Wognum, P.M., Trienekens, J.H., et al., 2012. Supply chain-wide consequences of transaction risks and their contractual solutions: towards an extended transaction cost economics framework. J. Supply Chain Manag., 48(1):73-91.
[25]Xu, N., Nozick, L., 2009. Modeling supplier selection and the use of option contracts for global supply chain design. Comput. Oper. Res., 36(10):2786-2800.
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