IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v199y2009i3p922-935.html
   My bibliography  Save this article

Robust multi-echelon multi-period inventory control

Author

Listed:
  • Aharon, Ben-Tal
  • Boaz, Golany
  • Shimrit, Shtern

Abstract

We consider the problem of minimizing the overall cost of a supply chain, over a possible long horizon, under demand uncertainly which is known only crudely. Under such circumstances, the method of choice is Robust Optimization, in particular the Affinely Adjustable Robust Counterpart (AARC) method which leads to tractable deterministic optimization problems. The latter is due to a recent re-parametrization technique for discrete time linear control systems. In this paper we model, analyze and test an extension of the AARC method known as the Globalized Robust Counterpart (GRC) in order to control inventories in serial supply chains. A simulation study demonstrates the merit of the methods employed here, in particular, it shows that a good control law that minimizes cost achieves simultaneously good control of the bullwhip effect.

Suggested Citation

  • Aharon, Ben-Tal & Boaz, Golany & Shimrit, Shtern, 2009. "Robust multi-echelon multi-period inventory control," European Journal of Operational Research, Elsevier, vol. 199(3), pages 922-935, December.
  • Handle: RePEc:eee:ejores:v:199:y:2009:i:3:p:922-935
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00211-2
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Blanchard, Olivier J, 1983. "The Production and Inventory Behavior of the American Automobile Industry," Journal of Political Economy, University of Chicago Press, vol. 91(3), pages 365-400, June.
    2. Aharon Ben-Tal & Boaz Golany & Arkadi Nemirovski & Jean-Philippe Vial, 2005. "Retailer-Supplier Flexible Commitments Contracts: A Robust Optimization Approach," Manufacturing & Service Operations Management, INFORMS, vol. 7(3), pages 248-271, February.
    3. Gérard P. Cachon & Taylor Randall & Glen M. Schmidt, 2007. "In Search of the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 457-479, April.
    4. Disney, S. M. & Towill, D. R. & van de Velde, W., 2004. "Variance amplification and the golden ratio in production and inventory control," International Journal of Production Economics, Elsevier, vol. 90(3), pages 295-309, August.
    5. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    6. Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
    7. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 2004. "Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect"," Management Science, INFORMS, vol. 50(12_supple), pages 1887-1893, December.
    8. John D. Sterman, 1989. "Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment," Management Science, INFORMS, vol. 35(3), pages 321-339, March.
    9. Charles C. Holt & Franco Modigliani & John P. Shelton, 1968. "The Transmission of Demand Fluctuations Through a Distribution and Production System, the Tv-Set Industry," Canadian Journal of Economics, Canadian Economics Association, vol. 1(4), pages 718-739, November.
    10. Gérard P. Cachon & Martin A. Lariviere, 2005. "Supply Chain Coordination with Revenue-Sharing Contracts: Strengths and Limitations," Management Science, INFORMS, vol. 51(1), pages 30-44, January.
    11. Christian Terwiesch & Z. Justin Ren & Teck H. Ho & Morris A. Cohen, 2005. "An Empirical Analysis of Forecast Sharing in the Semiconductor Equipment Supply Chain," Management Science, INFORMS, vol. 51(2), pages 208-220, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Minjiao Zhang & Simge Küçükyavuz & Saumya Goel, 2014. "A Branch-and-Cut Method for Dynamic Decision Making Under Joint Chance Constraints," Management Science, INFORMS, vol. 60(5), pages 1317-1333, May.
    2. Guerrero, W.J. & Yeung, T.G. & Guéret, C., 2013. "Joint-optimization of inventory policies on a multi-product multi-echelon pharmaceutical system with batching and ordering constraints," European Journal of Operational Research, Elsevier, vol. 231(1), pages 98-108.
    3. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    4. Gülpınar, Nalan & Pachamanova, Dessislava & Çanakoğlu, Ethem, 2013. "Robust strategies for facility location under uncertainty," European Journal of Operational Research, Elsevier, vol. 225(1), pages 21-35.
    5. Gorissen, Bram L. & den Hertog, Dick, 2013. "Robust counterparts of inequalities containing sums of maxima of linear functions," European Journal of Operational Research, Elsevier, vol. 227(1), pages 30-43.
    6. Oğuz Solyalı & Jean-François Cordeau & Gilbert Laporte, 2016. "The Impact of Modeling on Robust Inventory Management Under Demand Uncertainty," Management Science, INFORMS, vol. 62(4), pages 1188-1201, April.
    7. Xin, Linwei & Goldberg, David A., 2021. "Time (in)consistency of multistage distributionally robust inventory models with moment constraints," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1127-1141.
    8. Zhang, Wei & (Ato) Xu, Wangtu, 2017. "Simulation-based robust optimization for the schedule of single-direction bus transit route: The design of experiment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 203-230.
    9. Shin, Youngchul & Lee, Sangyoon & Moon, Ilkyeong, 2021. "Robust multiperiod inventory model with a new type of buy one get one promotion: “My Own Refrigerator”," Omega, Elsevier, vol. 99(C).
    10. Moshe Sniedovich, 2010. "A bird's view of info-gap decision theory," Journal of Risk Finance, Emerald Group Publishing, vol. 11(3), pages 268-283, May.
    11. Ali Haddad-Sisakht & Sarah M. Ryan, 2018. "Conditions under which adjustability lowers the cost of a robust linear program," Annals of Operations Research, Springer, vol. 269(1), pages 185-204, October.
    12. Shishebori, Davood & Yousefi Babadi, Abolghasem, 2015. "Robust and reliable medical services network design under uncertain environment and system disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 268-288.
    13. Almaraj, Ismail I. & Trafalis, Theodore B., 2019. "An integrated multi-echelon robust closed- loop supply chain under imperfect quality production," International Journal of Production Economics, Elsevier, vol. 218(C), pages 212-227.
    14. Oğuz Solyalı & Jean-François Cordeau & Gilbert Laporte, 2012. "Robust Inventory Routing Under Demand Uncertainty," Transportation Science, INFORMS, vol. 46(3), pages 327-340, August.
    15. Viktoryia Buhayenko & Dick den Hertog, 2017. "Adjustable Robust Optimisation approach to optimise discounts for multi-period supply chain coordination under demand uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6801-6823, November.
    16. Wenfen Zhang & Xinping Yan & Jiaqi Yang, 2017. "Optimized maritime emergency resource allocation under dynamic demand," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-23, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gérard P. Cachon & Taylor Randall & Glen M. Schmidt, 2007. "In Search of the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 457-479, April.
    2. Pastore, Erica & Alfieri, Arianna & Zotteri, Giulio, 2019. "An empirical investigation on the antecedents of the bullwhip effect: Evidence from the spare parts industry," International Journal of Production Economics, Elsevier, vol. 209(C), pages 121-133.
    3. Wang, Xun & Disney, Stephen M., 2016. "The bullwhip effect: Progress, trends and directions," European Journal of Operational Research, Elsevier, vol. 250(3), pages 691-701.
    4. Ma, Yungao & Wang, Nengmin & He, Zhengwen & Lu, Jizhou & Liang, Huigang, 2015. "Analysis of the bullwhip effect in two parallel supply chains with interacting price-sensitive demands," European Journal of Operational Research, Elsevier, vol. 243(3), pages 815-825.
    5. Li Chen & Hau L. Lee, 2012. "Bullwhip Effect Measurement and Its Implications," Operations Research, INFORMS, vol. 60(4), pages 771-784, August.
    6. Zhang, Xiaolong & Burke, Gerard J., 2011. "Analysis of compound bullwhip effect causes," European Journal of Operational Research, Elsevier, vol. 210(3), pages 514-526, May.
    7. Zotteri, Giulio, 2013. "An empirical investigation on causes and effects of the Bullwhip-effect: Evidence from the personal care sector," International Journal of Production Economics, Elsevier, vol. 143(2), pages 489-498.
    8. Isaksson, Olov H.D. & Seifert, Ralf W., 2016. "Quantifying the bullwhip effect using two-echelon data: A cross-industry empirical investigation," International Journal of Production Economics, Elsevier, vol. 171(P3), pages 311-320.
    9. Özelkan, Ertunga C. & Lim, Churlzu & Adnan, Ziaul Haq, 2018. "Conditions of reverse bullwhip effect in pricing under joint decision of replenishment and pricing," International Journal of Production Economics, Elsevier, vol. 200(C), pages 207-223.
    10. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    11. Pastore, Erica & Alfieri, Arianna & Zotteri, Giulio & Boylan, John E., 2020. "The impact of demand parameter uncertainty on the bullwhip effect," European Journal of Operational Research, Elsevier, vol. 283(1), pages 94-107.
    12. Nepal, Bimal & Murat, Alper & Babu Chinnam, Ratna, 2012. "The bullwhip effect in capacitated supply chains with consideration for product life-cycle aspects," International Journal of Production Economics, Elsevier, vol. 136(2), pages 318-331.
    13. Yuliang Yao & Kevin Xiaoguo Zhu, 2012. "Research Note ---Do Electronic Linkages Reduce the Bullwhip Effect? An Empirical Analysis of the U.S. Manufacturing Supply Chains," Information Systems Research, INFORMS, vol. 23(3-part-2), pages 1042-1055, September.
    14. Robert L. Bray & Haim Mendelson, 2012. "Information Transmission and the Bullwhip Effect: An Empirical Investigation," Management Science, INFORMS, vol. 58(5), pages 860-875, May.
    15. Sucky, Eric, 2009. "The bullwhip effect in supply chains--An overestimated problem?," International Journal of Production Economics, Elsevier, vol. 118(1), pages 311-322, March.
    16. Cantor, David E. & Katok, Elena, 2012. "Production smoothing in a serial supply chain: A laboratory investigation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 781-794.
    17. Zhu, Tianyuan & Balakrishnan, Jaydeep & da Silveira, Giovani J.C., 2020. "Bullwhip effect in the oil and gas supply chain: A multiple-case study," International Journal of Production Economics, Elsevier, vol. 224(C).
    18. Dominguez, Roberto & Cannella, Salvatore & Framinan, Jose M., 2015. "On returns and network configuration in supply chain dynamics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 152-167.
    19. Ouyang, Yanfeng & Li, Xiaopeng, 2010. "The bullwhip effect in supply chain networks," European Journal of Operational Research, Elsevier, vol. 201(3), pages 799-810, March.
    20. Minner, Stefan & Transchel, Sandra, 2017. "Order variability in perishable product supply chains," European Journal of Operational Research, Elsevier, vol. 260(1), pages 93-107.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:199:y:2009:i:3:p:922-935. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: http://www.elsevier.com/locate/eor .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.