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Designing a supply chain network under the risk of disruptions. (English) Zbl 1264.90017

Summary: We study a supply chain design problem with the risk of disruptions at facilities. At any point of time, the facilities are subject to various types of disruptions caused by natural disasters, man-made defections, and equipment breakdowns. We formulate the problem as a mixed-integer nonlinear program which maximizes the total profit for the whole system. The model simultaneously determines the number and location of facilities, the subset of customers to serve, the assignment of customers to facilities, and the cycle-order quantities at facilities. In order to obtain near-optimal solutions with reasonable computational requirements for large problem instances, two solution methods based on Lagrangian relaxation and genetic algorithm are developed. The effectiveness of the proposed solution approaches is shown using numerical experiments. The computational results, in addition, demonstrate that the benefits of considering disruptions in the supply chain design model can be significant.

MSC:

90B06 Transportation, logistics and supply chain management
90B50 Management decision making, including multiple objectives
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[1] M. S. Daskin, C. R. Coullard, and Z.-J. M. Shen, “An inventory-location model: formulation, solution algorithm and computational results,” Annals of Operations Research, vol. 110, no. 1-4, pp. 83-106, 2002. · Zbl 1013.90001
[2] J. Shu, C.-P. Teo, and Z.-J. M. Shen, “Stochastic transportation-inventory network design problem,” Operations Research, vol. 53, no. 1, pp. 48-60, 2005. · Zbl 1165.90367
[3] Z. J. Max Shen and L. Qi, “Incorporating inventory and routing costs in strategic location models,” European Journal of Operational Research, vol. 179, no. 2, pp. 372-389, 2007. · Zbl 1111.90012
[4] Z.-J. M. Shen, “Integrated supply chain design models: a survey and future research directions,” Journal of Industrial and Management Optimization, vol. 3, no. 1, pp. 1-27, 2007. · Zbl 1166.90346
[5] M. T. Melo, S. Nickel, and F. Saldanha-da-Gama, “Facility location and supply chain management-a review,” European Journal of Operational Research, vol. 196, no. 2, pp. 401-412, 2009. · Zbl 1163.90341
[6] Z. J. M. Shen, C. Coullard, and M. S. Daskin, “A joint location-inventory model,” Transportation Science, vol. 37, no. 1, pp. 40-55, 2003.
[7] L. V. Snyder, M. S. Daskin, and C. P. Teo, “The stochastic location model with risk pooling,” European Journal of Operational Research, vol. 179, no. 3, pp. 1221-1238, 2007. · Zbl 1127.90039
[8] L. Ozsen, C. R. Coullard, and M. S. Daskin, “Capacitated warehouse location model with risk pooling,” Naval Research Logistics, vol. 55, no. 4, pp. 295-312, 2008. · Zbl 1153.90484
[9] L. Ozsen, M. S. Daskin, and C. R. Coullard, “Facility location modeling and inventory management with multisourcing,” Transportation Science, vol. 43, no. 4, pp. 455-472, 2009.
[10] P. A. Miranda and R. A. Garrido, “Inventory service-level optimization within distribution network design problem,” International Journal of Production Economics, vol. 122, no. 1, pp. 276-285, 2009.
[11] Z. Yao, L. H. Lee, W. Jaruphongsa, V. Tan, and C. F. Hui, “Multi-source facility location-allocation and inventory problem,” European Journal of Operational Research, vol. 207, no. 2, pp. 750-762, 2010. · Zbl 1205.90178
[12] S. Park, T. E. Lee, and C. S. Sung, “A three-level supply chain network design model with risk-pooling and lead times,” Transportation Research Part E, vol. 46, no. 5, pp. 563-581, 2010.
[13] K. Sweet, “China earthquake hits home for u.s. companies,” Fox Business, May 2008.
[14] A. Latour, “Trial by fire: a blaze in Albuquerque sets off major crisis for cell-phone giants-Nokia handles supply chain shock with aplomb as Ericsson of Sweden gets burned- Was Sisu the difference?” Wall Street Journal, January 2001.
[15] D. Leonard, “The only lifeline was the wal-mart,” Fortune, vol. 152, no. 7, pp. 74-80, 2005.
[16] L. V. Snyder and M. S. Daskin, “Reliability models for facility location: the expected failure cost case,” Transportation Science, vol. 39, no. 3, pp. 400-416, 2005.
[17] O. Berman, D. Krass, and M. B. C. Menezes, “Facility reliability issues in network p-median problems: strategic centralization and co-location effects,” Operations Research, vol. 55, no. 2, pp. 332-350, 2007. · Zbl 1167.90466
[18] M. Lim, M. S. Daskin, A. Bassamboo, and S. Chopra, “A facility reliability problem: formulation, properties, and algorithm,” Naval Research Logistics, vol. 57, no. 1, pp. 58-70, 2010. · Zbl 1180.90090
[19] T. Cui, Y. Ouyang, and Z.-J. M. Shen, “Reliable facility location design under the risk of disruptions,” Operations Research, vol. 58, no. 4, part 1, pp. 998-1011, 2010. · Zbl 1231.90266
[20] F. Liberatore, M. P. Scaparra, and M. S. Daskin, “Analysis of facility protection strategies against an uncertain number of attacks: the stochastic R-interdiction median problem with fortification,” Computers & Operations Research, vol. 38, no. 1, pp. 357-366, 2011. · Zbl 1231.90268
[21] P. Peng, L. V. Snyder, A. Lim, and Z. Liu, “Reliable logistics networks design with facility disruptions,” Transportation Research Part B, vol. 45, no. 8, pp. 1190-1211, 2011.
[22] L. V. Snyder, M. P. Scaparra, M. S. Daskin, and R. L. Church, “Planning for disruptions in supply chain networks,” in TutORials in Operations Research, P. Johnson, B. Norman, and N. Secomandi, Eds., pp. 234-257, INFORMS, Baltimore, Md, USA, 2006.
[23] L. V. Snyder and M. S. Daskin, “Models for reliable supply chain network design,” in Critical Infrastructure: Reliability and Vulnerability, A. T. Murray and T. H. Grubesic, Eds., pp. 257-289, Springer, Berlin, Germany, 2007.
[24] M. B. Aryanezhad, S. G. Jalali, and A. Jabbarzadeh, “An integrated supply chain design model with random disruptions consideration,” African Journal of Business Management, vol. 4, no. 12, pp. 2393-2401, 2010.
[25] Q. Chen, X. Li, and Y. Ouyang, “Joint inventory-location problem under the risk of probabilistic facility disruptions,” Transportation Research Part B, vol. 45, no. 7, pp. 991-1003, 2011.
[26] L. Qi and Z.-J. M. Shen, “A supply chain design model with unreliable supply,” Naval Research Logistics, vol. 54, no. 8, pp. 829-844, 2007. · Zbl 1135.90361
[27] L. Qi, Z. J. M. Shen, and L. V. Snyder, “The effect of supply disruptions on supply chain design decisions,” Transportation Science, vol. 44, no. 2, pp. 274-289, 2010.
[28] Z.-J. M. Shen, “A profit-maximizing supply chain network design model with demand choice flexibility,” Operations Research Letters, vol. 34, no. 6, pp. 673-682, 2006. · Zbl 1112.90013
[29] P. Zipkin, Foundations of Inventory Management, McGraw-Hill, Irwin, Calif, USA, 2000. · Zbl 1370.90005
[30] J. H. Jaramillo, J. Bhadury, and R. Batta, “On the use of genetic algorithms to solve location problems,” Computers & Operations Research, vol. 29, no. 6, pp. 761-779, 2002. · Zbl 0995.90060
[31] O. Alp, E. Erkut, and Z. Drezner, “An efficient genetic algorithm for the p-median problem,” Annals of Operations Research, vol. 122, pp. 21-42, 2003. · Zbl 1038.90046
[32] T. Drezner, Z. Drezner, and S. Salhi, “Solving the multiple competitive facilities location problem,” European Journal of Operational Research, vol. 142, no. 1, pp. 138-151, 2002. · Zbl 1081.90575
[33] M. B. Aryanezhad, S. G. Jalali, and A. Jabbarzadeh, “An integrated location inventory model for designing a supply chain network under uncertainty,” Life Science Journal, vol. 8, no. 4, pp. 670-679, 2011.
[34] K. Sourirajan, L. Ozsen, and R. Uzsoy, “A genetic algorithm for a single product network design model with lead time and safety stock considerations,” European Journal of Operational Research, vol. 197, no. 2, pp. 599-608, 2009. · Zbl 1159.90389
[35] H. Min, H. J. Ko, and C. S. Ko, “A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns,” Omega, vol. 34, no. 1, pp. 56-69, 2006.
[36] J. Current, M. Daskin, and D. Schilling, “Discrete network location models,” in Facility Location: Applications and Theory, Z. Drezner and H. W. Hamacher, Eds., pp. 83-120, Springer, Berlin, Germany, 2001.
[37] M. L. Fisher, “The Lagrangian relaxation method for solving integer programming problems,” Management Science, vol. 27, no. 1, pp. 1-18, 1981. · Zbl 0539.90079
[38] M. L. Fisher, “An applications oriented guide to Lagrangian relaxation,” Interfaces, vol. 15, no. 2, pp. 10-21, 1985.
[39] M. Gen and R. Cheng, Genetic Algorithms and Engineering Design, Wiley, New York, NY, USA, 1996.
[40] M. Gen and R. Cheng, Genetic Algorithms and Engineering Optimization, Wiley, New York, NY, USA, 2000.
[41] M. S. Daskin, Network and Discrete Location: Models, Algorithms, and Applications, Wiley-Interscience Series in Discrete Mathematics and Optimization, John Wiley & Sons, New York, NY, USA, 1995. · Zbl 0870.90076
[42] J. J. Grefenstette, “Optimization of control parameters for genetic algorithms,” IEEE Transactions on Systems, Man and Cybernetics, vol. 16, no. 1, pp. 122-128, 1986.
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