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Selection of a dynamic supply portfolio in make-to-order environment with risks. (English) Zbl 1202.90166
Summary: The problem of a multi-period supplier selection and order allocation in make-to-order environment in the presence of supply chain disruption and delay risks is considered. Given a set of customer orders for finished products, the decision maker needs to decide from which supplier and when to purchase product-specific parts required for each customer order to meet customer requested due date at a low cost and to mitigate the impact of supply chain risks. The selection of suppliers and the allocation of orders over time is based on price and quality of purchased parts and reliability of supplies. For selection of dynamic supply portfolio a mixed integer programming approach is proposed to incorporate risk that uses conditional value-at-risk via scenario analysis. In the scenario analysis, the low-probability and high-impact supply disruptions are combined with the high probability and low impact supply delays. The proposed approach is capable of optimizing the dynamic supply portfolio by calculating value-at-risk of cost per part and minimizing expected worst-case cost per part simultaneously. Numerical examples are presented and some computational results are reported.
MSC:
90B50Management decision making, including multiple objectives
91B30Risk theory, insurance
90C11Mixed integer programming
90B06Transportation, logistics
References:
[1]Tang, C. S.: Perspectives in supply chain risk management, International journal of production economics 103, 451-488 (2006)
[2]Norrman, A.; Jansson, U.: Ericsson’s proactive risk management approach after a serious sub-supplier accident, International journal of physical distribution and logistics management 34, No. 5, 434-456 (2004)
[3]Sheffi, Y.: The resilient enterprise, (2005)
[4]Kleindorfer, P. R.; Saad, G. H.: Managing disruption risks in supply chains, Production and operations management 4, No. 1, 53-68 (2005)
[5]Oke, A.; Gopalakrishnan, M.: Managing disruptions in supply chains: a case study of a retail supply chain, International journal of production economics 118, 168-174 (2009)
[6]Kasilingam, R. G.; Lee, C. P.: Selection of vendors–a mixed-integer programming approach, Computers and industrial engineering 31, 347-350 (1996)
[7]Wu, D.; Olson, D. L.: Supply chain risk, simulation, and vendor selection, International journal of production economics 114, 646-655 (2008)
[8]Berger, P. D.; Gerstenfeld, A.; Zeng, A. Z.: How many suppliers are best? A decision-analysis approach, Omega: the international journal of management science 32, No. 1, 9-15 (2004)
[9]Ruiz-Torres, A. J.; Farzad, M.: The optimal number of suppliers considering the costs of individual supplier failures, Omega: the international journal of management science 35, No. 1, 104-115 (2007)
[10]Berger, P. D.; Zeng, A. Z.: Single versus multiple sourcing in the presence of risks, Journal of the operational research society 57, No. 3, 250-261 (2006) · Zbl 1089.90031 · doi:10.1057/palgrave.jors.2601982
[11]Yu, H.; Zeng, A. Z.; Zhao, L.: Single or dual sourcing: decision-making in the presence of supply chain disruption risks, Omega: the international journal of management science 37, 788-800 (2009)
[12]Li L, Zabinsky ZB. Incorporating uncertainty into a supplier selection problem. International Journal of Production Economics 2009; doi:10.1016/j.ijpe.2009.11.007.
[13]Aissaoui, N.; Haouari, M.; Hassini, E.: Supplier selection and order lot sizing modeling: a review, Computers & operations research 34, 3516-3540 (2007) · Zbl 1128.90033 · doi:10.1016/j.cor.2006.01.016
[14]Akinc, U.: Selecting a set of vendors in a manufacturing environment, Journal of operations management 11, 107-122 (1993)
[15]Murthy, N. N.; Soni, S.; Ghosh, S.: A framework for facilitating sourcing and allocation decisions for make-to-order items, Decision sciences 35, 237-259 (2004)
[16]Sawik, T.: A cyclic versus flexible approach to materials ordering in make-to-order assembly, Mathematical and computer modelling 42, 279-290 (2005) · Zbl 1090.90108 · doi:10.1016/j.mcm.2005.03.002
[17]Sawik, T.: Single vs. Multiple objective supplier selection in a make-to-order environment, Omega: the international journal of management science 38, No. 3–4, 203-212 (2010)
[18]Sawik, T.: Selection of supply portfolio under disruption risks, Omega: the international journal of management science 39, 194-208 (2011)
[19]Yue, J.; Xia, Y.; Tran, T.: Selecting sourcing partners for a make-to-order supply chain, Omega: the international journal of management science 38, No. 3-4, 136-144 (2010)
[20]Basnet, C.; Leung, J. M. Y.: Inventory lot-sizing with supplier selection, Computers & operations research 32, 1-14 (2005) · Zbl 1076.90002 · doi:10.1016/S0305-0548(03)00199-0
[21]Xia, W.; Wu, Z.: Supplier selection with multiple criteria in volume discount environments, Omega: the international journal of management science 35, 494-504 (2007)
[22]Demirtas, E. A.; Ustun, O.: An integrated multiobjective decision making process for supplier selection and order allocation, Omega: the international journal of management science 36, 76-90 (2008)
[23]Ustun, O.; Demirtas, E. A.: An integrated multi-objective decision making process for multi-period lot sizing with supplier selection, Omega: the international journal of management science 36, 509-521 (2008)
[24]Che, Z. H.; Wang, H. S.: Supplier selection and supply quantity allocation of common and non-common parts with multiple criteria under multiple products, Computers and industrial engineering 55, 110-133 (2008)
[25]Uryasev, S.: Conditional value-at-risk: optimization algorithms and applications, Financial engineering news 14, No. 2, 1-5 (2000)
[26]Rockafellar, R. T.; Uryasev, S.: Optimization of conditional value-at-risk, The journal of risk 2, No. 3, 21-41 (2000)
[27]Rockafellar, R. T.; Uryasev, S.: Conditional value-at-risk for general loss distributions, Journal of banking and finance 26, No. 7, 1443-1471 (2002)
[28]Gotoh, J.; Takano, Y.: Newsvendor solutions via conditional value-at-risk minimization, European journal of operational research 179, No. 1, 80-96 (2007)
[29]Chahar, K.; Taaffe, K.: Risk averse demand selection with all-or-nothing orders, Omega. the international journal of management science 37, No. 5, 996-1006 (2009)