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Coordination of a supply chain with one-manufacturer and two-retailers under demand promotion and disruption management decisions. (English) Zbl 1112.90305
Summary: Increasingly, customer service, rapid response to customer requirements, and flexibility to handle uncertainties in both demand and supply are becoming strategic differentiators in the marketplace. Organizations that want to achieve these benchmarks require sophisticated approaches to conduct order promising and fulfillment, especially in todays high-mix low-volume production environment. Motivated by these challenges, the Available-to-Promise (ATP) function has migrated from a set of availability records in a Master Production Schedule (MPS) toward an advanced real-time decision support system to enhance decision responsiveness and quality in Assembly To Order (ATO) or Configuration To Order (CTO) environments. Advanced ATP models and systems must directly link customer orders with various forms of available resources, including both material and production capacity. In this paper, we describe a set of enhancements carried out to adapt previously published mixed-integer-programming (MIP) models to the specific requirements posed by an electronic product supply chain within Toshiba Corporation. This model can provide individual order delivery quantities and due dates, together with production schedules, for a batch of customer orders that arrive within a predefined batching interval. The model considers multi-resource availability including manufacturing orders, production capability and production capacity. In addition, the model also takes into account a variety of realistic order promising issues such as order splitting, model decomposition and resource expediting and de-expediting. We conclude this paper with comparison of our model execution results vs. actual historical performance of systems currently in place.

90B05 Inventory, storage, reservoirs
90B30 Production models
90B50 Management decision making, including multiple objectives
Full Text: DOI
[1] Cachon, G.P. and M.A. Lariviere. (1999). ”Capacity Choice and Allocation: Strategic Behavior and Supply Chain Performance.” Management Science 45(8), 1091–1108. · Zbl 1231.90012 · doi:10.1287/mnsc.45.8.1091
[2] Cachon, G.P. (2002). ”The Allocation of Inventory Risk and Advanced Purchase Discounts in a Supply Chain.” The Wharton School, University of Pennsylvania, Working Paper.
[3] Celikbas, M., J.G. Shanthikumar, and J.M. Swaminathan. (1999). ”Coordinating Production Quantities and Demand Forecasts through Penalty Schemes.” IIE Transactions 31, 851–864.
[4] Corbett, C.J. and G.A. DeCroix. (2001). ”Shared-Savings Contracts for Indirect Materials in Supply Chains: Channel Profits and Environmental Impacts.” Management Science 47(7), 881–893. · Zbl 1232.90271 · doi:10.1287/mnsc.47.7.881.9802
[5] Gilbert, S., Y. Xia, and G. Yu. (2002). ”Strategic Interactions Between Channel Structure and Control of Value-Added Services.” Red-McCombs School of Business, The University of Texas at Austin, Working Paper.
[6] Iyer, G. (1998). ”Coordinating Channels under Price and Non-price Competition.” Marketing Science 17(4), 338–355. · doi:10.1287/mksc.17.4.338
[7] Perry, M. and R. Porter. (1990). ”Can Resale Price Maintenance Franchise Fees Correct Sub-optimal Levels of Retailer Service.” International Journal of Industrial Organization 8, 115–141. · doi:10.1016/0167-7187(89)90037-4
[8] Qi, X., J.F. Bard, and G. Yu. (2004). ”Supply Chain Coordination with Demand Disruptions.” Omega 32, 301–312. · doi:10.1016/j.omega.2003.12.002
[9] Taylor, T.A. (2002). ”Supply Chain Coordination under Channel Rebates with Sales Effort Effects.” Management Science 48(8), 992–1007. · Zbl 1232.90198 · doi:10.1287/mnsc.48.8.992.168
[10] Tirole, J. (1988). The Theory of Industrial Organization.Cambridge, MA: The MIT Press. · Zbl 0664.90023
[11] Treece, J. (1997). ”Just-too-much Single-sourcing spurs Toyota Purchasing Review: Maker Seeks at Least 2 Suppliers for Each Part.” Automotive News,March 3.
[12] Tsay, A.A. (1999). ”The Quantity Flexibility Contract and Supplier-Customer Incentives.” Management Science 45(10), 1339–1358. · Zbl 1231.90065 · doi:10.1287/mnsc.45.10.1339
[13] Tsay, A. and N. Aggrawal. (2000). ”Channel Dynamics under Price and Service Competition.” Manufacturing & Service Operations Management 2(4), 372–391. · doi:10.1287/msom.2.4.372.12342
[14] Ugarte, A. and S. Oren. (2000). ”Coordination of Internal Supply Chains in Vertically Integrated High-Tech Manufacturing Organizations (HTMOs).” International Journal of Production Economics 67, 235–252. · doi:10.1016/S0925-5273(00)00022-0
[15] Wang, Y. and Y. Gerchak. (2001).”Supply Chain Coordination when Demand is Shelf-Space-Dependent.” Manufacturing & Service Operations Management 3(1), 82–87. · doi:10.1287/msom.
[16] Xia, Y.S., X.T. Qi, and G. Yu. (2002). ”Real-Time Production and Inventory Disruption Management under the Continuous Rate Economic Production Quantity Model.” Red-McCombs School of Business, the University of Texas at Austin, Working Paper.
[17] Xia, Y.S., M. Yang, B. Golany, S. Gilbert, and G. Yu. (2004). ”Real-Time Disruption Management in a Two-Stage Production and Inventory System.” IIE Transactions 36, 111–125. · doi:10.1080/07408170490245379
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