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The demand disruption management problem for a supply chain system with nonlinear demand functions

Abstract

This paper addresses the problem of handling the uncertainty of demand in a one-supplier-one-retailer supply chain system. Demand variation often makes the real production different from what is originally planned, causing a deviation cost from the production plan. Assume the market demand is sensitive to the retail price in a nonlinear form, we show how to effectively handle the demand uncertainty in a supply chain, both for the case of centralized-decision-making system and the case of decentralized-decision-making system with perfect coordination.

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References

  1. [1]

    Boyaci, T. and Gallego, “Coordinating pricing and inventory replenishment policies for one wholesaler and one or more geographically dispersed retailers”, International Journal of Production Economics, Vol. 77, pp95–111, 2002.

    Article  Google Scholar 

  2. [2]

    Chen F., A. Federgruen and Y.-S. Zheng, “Coordination mechanisms for a distribution system with one supplier and multiple retailers”, Management Science, Vol. 47, No. 5, pp693–708, 2002.

    Article  Google Scholar 

  3. [3]

    Cliausen, J., J. Hansen, J. Lansen and A. Larsen, “sruption management”, ORMS Today, Vol. 28, No 5, pp40–43, 2001.

    Google Scholar 

  4. [4]

    Jeuland, A. and S. Shugan, “Managing channel profits”, Marketing Science, Vol. 2, pp239–272, 1983.

    Article  Google Scholar 

  5. [5]

    Milner, J.M. and M.J. Rosenblatt, “Flexible supply contracts for short life-cycle goods: The buyers’s perspective”, Naval Research Logistics, Vol. 49, No. 1, pp25–45, 2002.

    MATH  MathSciNet  Article  Google Scholar 

  6. [6]

    Qi, X., J.F. Bard and G. Yu, Supply chain coordination with demand disruptions, Working paper, Department of Management Science and Information Systems, McCombs School of Business, The University of Texas, Austin, TX. 78712, 2002(a).

    Google Scholar 

  7. [7]

    Qi, X., J.F. Bard and G. Yu, Disruption management for machine scheduling: the case of SPT schedules, Working paper, Department of Management Science and Information Systems, McCombs School of Business, The University of Texas, Austin, TX. 78712, 2002(b).

    Google Scholar 

  8. [8]

    Thengvall, B., J.F. Bard and G. Yu, “Balancing user preferences for aircraft schedule recovery during irregular operations”, IIE Transactions on Operations Engineering, Vol. 32, No. 3, pp181–193, 2000.

    Google Scholar 

  9. [9]

    Weng, K, “Channel coordination and quantity discounts”, Management Science, Vol. 41, No. 9, pp1509–1522, 1995.

    MATH  MathSciNet  Google Scholar 

  10. [10]

    Yang, J., X. Qi and G. Yu, Disruption management in production planning, Working paper, Department of Management Science and Information Systems, McCombs School of Business, The University of Texas, Austin, TX. 78712, 2001.

    Google Scholar 

  11. [11]

    Yu, G., M. Argüello, G. Song, S. M. McCowan, and A. White, A new era for crew recovery at continental airlines, to appear in Interfaces, 2002

Download references

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Supported by NSFC (79928001, A0224017, 79870091)

Minghui Xu is a Ph.D. Candidate of School of Mathematics and Stochastic in Wuhan University. He obtained his bachelor and master degrees from School of Mathematics and Stochastic in Wuhan University in 1998 and 2001 respectively. His research interests include applied optimization and applications in supply chain management, disruption management and other managerial areas.

Xiangtong Qi is a Ph.D. candidate in the Department of Management Science and Information Systems of The University of Texas at Austin. He obtained his bachelor, master and doctorate degree from Department of Computer and System Sciences of Nankai University in 1992, 1995, and 1998 respectively. His research interests include modeling and optimization with applications in manufacturing systems, supply chain management, and airlines. He has published papers in Discrete Applied Mathematics, European Journal of Operational Research, Journal of the Operational Research Society, and others.

Gang Yu is currently the Jack G. Taylor Regents Professor in Business at McCombs School of Business at The University of Texas at Austin. He received M.S. from Cornell University and Ph.D. from the Wharton School, University of Pennsylvania. He is the author of over 70 journal articles and 4 books, and he serves on five editorial boards. He consults for over a dozen Fortune 500 companies including IBM, United Airlines, EDS, Tracor Applied Sciences, Ameritech, and Continental Airlines. He is the Founder and former Chairman and CEO of CALEB Technologies. He recently won the Franz Edelman Management Science Achievement Award.

Hanqin Zhang is currently a full professor of the Chinese Academy of Sciences. He received his PhD in 1991 from the Institute of Applied Mathematics, Chinese Academy of Sciences. He has visited and worked at Marburg University, University of British Columbia, University of Toronto, University of Texas, the Chinese University of Hong Kong, and other institutions. He has been on the editorial board of Acta Mathematics Applicatae Sinica (English Series and Chinese Series), Systems Science and Mathematical Sciences, Journal of Systems Science and Complexity, and IEEE Transactions on Automatic Controls. His areas of research interests include stochastic manufacturing systems, stochastic optimal control, queuing networks and supply chain management.

Chengxiu Gao is a professor of Applied Mathematics, vice director of International Research Center for Management of Operation and Logistics, Wuhan University. His areas of research interests include system optimization, decision making for management and mathematical modeling.

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Xu, M., Qi, X., Yu, G. et al. The demand disruption management problem for a supply chain system with nonlinear demand functions. J. Syst. Sci. Syst. Eng. 12, 82–97 (2003). https://doi.org/10.1007/s11518-006-0122-x

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Keywords

  • Supply chain management
  • disruption management
  • demand uncertainty