Using Imperfect Advance Demand Information in Production-Inventory Systems with Multiple Customer Classes

Published Online:https://doi.org/10.1287/msom.1070.0201

References

  • Benjaafar S., Elhafsi M. Production and inventory control of a single product assemble-to-order system with multiple customer classes. Management Sci. (2006) 52:1896–1912LinkGoogle Scholar
  • Benjaafar S., Cooper W. L., Mardan S. Production-inventory systems with imperfect advance demand information and updating. (2007) . Working Paper, University of Minnesota, MinneapolisGoogle Scholar
  • Benjaafar S., Elhafsi M., de Véricourt F. Demand allocation in multi-product, multi-facility make-to-stock systems. Management Sci. (2004) 50:1431–1448LinkGoogle Scholar
  • Bertsekas D.Dynamic Programming and Optimal Control (2001) 22nd ed.(Athena Scientific, Nashua, NH) Optimization and Computation SeriesGoogle Scholar
  • Buzacott J. A., Shanthikumar J. G.Stochastic Models of Manufacturing Systems (1993) (Prentice-Hall, Upper Saddle River, NJ) Google Scholar
  • Buzacott J. A., Shanthikumar J. G. Safety stock versus safety time in MRP controlled production systems. Management Sci. (1994) 40:1678–1689LinkGoogle Scholar
  • Chen F. Market segmentation, advance demand information, and supply chain performance. Manufacturing Service Oper. Management (2001) 3:53–67LinkGoogle Scholar
  • Cohen M. A., Kleindorfer P. R., Lee H. L. Service constrained (s, S) inventory systems with priority demand classes and lost sales. Management Sci. (1988) 34:482–499LinkGoogle Scholar
  • de Véricourt F., Karaesmen F., Dallery Y. Stock allocation for a capacitated supply system. Management Sci. (2002) 48:1486–1501LinkGoogle Scholar
  • Deshpande V., Cohen M. A., Donohue K. A threshold inventory rationing policy for service-differentiated demand classes. Management Sci. (2003) 49:683–703LinkGoogle Scholar
  • Frank K. C., Zhang R. Q., Duenyas I. Optimal policies for inventory systems with priority demand classes. Oper. Res. (2003) 51:993–1002LinkGoogle Scholar
  • Gallego G., Ozer O. Integrating replenishment decisions with advance order information. Management Sci. (2001) 47:1344–1360LinkGoogle Scholar
  • Gallego G., Ozer O., Song J. S., Yao D. D. Optimal use of demand information in supply chain management. Supply Chain Structures: Coordination, Information and Optimization (2002) (Kluwer Academic, Norwell, MA) 119–160CrossrefGoogle Scholar
  • Graves S. C., Meal H. C., Dasu S., Qiu Y., Axsäter S., Schneeweiss C., Silver E. Two-stage production planning in a dynamic environment. Multi-Stage Production Planning and Control—Lecture Notes in Economics and Mathematical Systems (1986) (Springer-Verlag, Berlin) 9–43CrossrefGoogle Scholar
  • Güllü R. On the value of information in dynamic production/inventory problems under forecast evolution. Naval Res. Logist. (1996) 43:289–303CrossrefGoogle Scholar
  • Guo X., Hernández-Lerma O. Continuous-time controlled Markov chains with discounted rewards. Acta Applicandae Mathematicae (2003) 79:195–216CrossrefGoogle Scholar
  • Ha A. Y. Inventory rationing in a make-to-stock production system with several demand classes and lost sales. Management Sci. (1997a) 43:1093–1103LinkGoogle Scholar
  • Ha A. Y. Stock-rationing policy for a make-to-stock production system with two priority classes and backordering. Naval Res. Logist. (1997b) 44:457–472CrossrefGoogle Scholar
  • Hariharan R., Zipkin P. Customer-order information, leadtimes and inventories. Management Sci. (1995) 41:1599–1607LinkGoogle Scholar
  • Heath D. C., Jackson P. L. Modeling the evolution of demand forecasts with application to safety-stock analysis in production/distribution systems. IIE Trans. (1994) 26:17–30CrossrefGoogle Scholar
  • Hu X., Duenyas I., Kapuscinki R. Advance demand information and safety capacity as a hedge against demand and capacity uncertainty. (2003) . Working paper, University of Michigan, Ann ArborLinkGoogle Scholar
  • Karaesmen F., Buzacott J. A., Dallery Y. Integrating advance order information in production control. IIE Trans. (2002) 34:649–662CrossrefGoogle Scholar
  • Karaesmen F., Liberopoulos G., Dallery Y. The value of advance demand information in production/inventory systems. Ann. Oper. Res. (2004) 126:135–158CrossrefGoogle Scholar
  • Lippman S. Applying a new device in the optimization of exponential queueing systems. Oper. Res. (1975) 23:687–710LinkGoogle Scholar
  • Nahmias S., Demmy S. Operating characteristics of an inventory system with rationing. Management Sci. (1981) 27:1236–1245LinkGoogle Scholar
  • Özer O., Wei W. Inventory control with limited capacity and advance demand information. Oper. Res. (2004) 52:988–1000LinkGoogle Scholar
  • Puterman M.Markov Decision Processes: Discrete Stochastic Dynamic Programming (1994) (John Wiley and Sons, Inc., New York) CrossrefGoogle Scholar
  • Schwarz L. B., Petruzzi N. C., Wee K. The value of advance-order information and the implications for managing the supply chain: An information/control/buffer portfolio perspective. (1997) . Working paper, Purdue University, West Lafayette, INGoogle Scholar
  • Tan T., Güllü R., Erkip N. Using imperfect advance demand information in ordering and rationing decisions. (2005) . Working paper, Eindhoven University of Technology, The NetherlandsGoogle Scholar
  • Topkis D. M. Optimal ordering and rationing policies in a nonstationary dynamic inventory model with n demand classes. Management Sci. (1968) 15:160–176LinkGoogle Scholar
  • van Donselaar K., Kopzcak L. R., Wouters M. The use of advance demand information in a project-based supply chain. Eur. J. Oper. Res. (2001) 130:519–538CrossrefGoogle Scholar
  • Veatch M. H., Wein L. M. Monotone control of queueing networks. Queueing Systems (1992) 12:391–408CrossrefGoogle Scholar
  • Zhu K., Thonemann U. Modeling the benefits of sharing future demand information. Oper. Res. (2004) 52:136–147LinkGoogle Scholar
  • Zipkin P. H.Foundations of Inventory Management (2000) (McGraw-Hill, New York) Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.