IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v49y2019i5p355-370.html
   My bibliography  Save this article

Primal–Dual Algorithms for Order Fulfillment at Urban Outfitters, Inc

Author

Listed:
  • John M. Andrews

    (Celect, Inc., Boston, Massachusetts 02110;)

  • Vivek F. Farias

    (Celect, Inc., Boston, Massachusetts 02110; MIT, Cambridge, Massachusetts 02139;)

  • Aryan I. Khojandi

    (Celect, Inc., Boston, Massachusetts 02110;)

  • Chad M. Yan

    (Celect, Inc., Boston, Massachusetts 02110)

Abstract

We formulate the omni-channel fulfillment problem as an online optimization problem. We propose a novel algorithm for this problem based on the primal–dual schema. Our algorithm is robust: It does not require explicit demand forecasts. This is an important practical advantage in the apparel-retail setting, where demand is volatile and unpredictable. We provide a performance analysis establishing that our algorithm admits optimal performance guarantees in the face of adversarial demand. We describe a large-scale implementation of our algorithm at Urban Outfitters, Inc. This implementation processes on average 18,000 customer orders a day and as many as 100,000 orders on peak demand days. The system has resulted in substantial savings relative to an incumbent industry-standard fulfillment optimization implementation through optimal order-fulfillment decisions that simultaneously increase turn and lower shipping costs.

Suggested Citation

  • John M. Andrews & Vivek F. Farias & Aryan I. Khojandi & Chad M. Yan, 2019. "Primal–Dual Algorithms for Order Fulfillment at Urban Outfitters, Inc," Interfaces, INFORMS, vol. 49(5), pages 355-370, September.
    • Handle: RePEc:inm:orinte:v:49:y:2019:i:5:p:355-370
    DOI: 10.1287/inte.2019.1013
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/inte.2019.1013
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.2019.1013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Daniel Adelman, 2007. "Dynamic Bid Prices in Revenue Management," Operations Research, INFORMS, vol. 55(4), pages 647-661, August.
    2. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    3. Mahar, Stephen & Bretthauer, Kurt M. & Venkataramanan, M.A., 2009. "The value of virtual pooling in dual sales channel supply chains," European Journal of Operational Research, Elsevier, vol. 192(2), pages 561-575, January.
    4. Daniel Adelman, 2004. "A Price-Directed Approach to Stochastic Inventory/Routing," Operations Research, INFORMS, vol. 52(4), pages 499-514, August.
    5. Guillermo Gallego & Garrett van Ryzin, 1997. "A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management," Operations Research, INFORMS, vol. 45(1), pages 24-41, February.
    6. Alptekinoglu, Aydin & Tang, Christopher S., 2005. "A model for analyzing multi-channel distribution systems," European Journal of Operational Research, Elsevier, vol. 163(3), pages 802-824, June.
    7. Hau L. Lee, 1987. "A Multi-Echelon Inventory Model for Repairable Items with Emergency Lateral Transshipments," Management Science, INFORMS, vol. 33(10), pages 1302-1316, October.
    8. Dan Zhang & Daniel Adelman, 2009. "An Approximate Dynamic Programming Approach to Network Revenue Management with Customer Choice," Transportation Science, INFORMS, vol. 43(3), pages 381-394, August.
    9. Jayashankar M. Swaminathan & Sridhar R. Tayur, 2003. "Models for Supply Chains in E-Business," Management Science, INFORMS, vol. 49(10), pages 1387-1406, October.
    10. Paterson, Colin & Kiesmüller, Gudrun & Teunter, Ruud & Glazebrook, Kevin, 2011. "Inventory models with lateral transshipments: A review," European Journal of Operational Research, Elsevier, vol. 210(2), pages 125-136, April.
    11. Michael O. Ball & Maurice Queyranne, 2009. "Toward Robust Revenue Management: Competitive Analysis of Online Booking," Operations Research, INFORMS, vol. 57(4), pages 950-963, August.
    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. Alisha Lakra & Shubhkirti Gupta & Ravi Ranjan & Sushanta Tripathy & Deepak Singhal, 2022. "The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach," Logistics, MDPI, vol. 6(4), pages 1-15, October.
    2. Jia Guo & Burcu B. Keskin, 2023. "Designing a centralized distribution system for omni‐channel retailing," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1724-1742, June.
    3. Hübner, Alexander & Hense, Jonas & Dethlefs, Christian, 2022. "The revival of retail stores via omnichannel operations: A literature review and research framework," European Journal of Operational Research, Elsevier, vol. 302(3), pages 799-818.
    4. Meng Qi & Ho‐Yin Mak & Zuo‐Jun Max Shen, 2020. "Data‐driven research in retail operations—A review," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(8), pages 595-616, 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. Thomas W. M. Vossen & Dan Zhang, 2015. "Reductions of Approximate Linear Programs for Network Revenue Management," Operations Research, INFORMS, vol. 63(6), pages 1352-1371, December.
    2. Wuyang Yuan & Lei Nie & Xin Wu & Huiling Fu, 2018. "A dynamic bid price approach for the seat inventory control problem in railway networks with consideration of passenger transfer," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-23, August.
    3. Dan Zhang & Zhaosong Lu, 2013. "Assessing the Value of Dynamic Pricing in Network Revenue Management," INFORMS Journal on Computing, INFORMS, vol. 25(1), pages 102-115, February.
    4. Mika Sumida & Huseyin Topaloglu, 2019. "An Approximation Algorithm for Capacity Allocation Over a Single Flight Leg with Fare-Locking," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 83-99, February.
    5. Zizhuo Wang & Yinyu Ye, 2016. "Hidden-City Ticketing: The Cause and Impact," Transportation Science, INFORMS, vol. 50(1), pages 288-305, February.
    6. Dan Zhang & Larry Weatherford, 2017. "Dynamic Pricing for Network Revenue Management: A New Approach and Application in the Hotel Industry," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 18-35, February.
    7. Dragos Florin Ciocan & Vivek Farias, 2012. "Model Predictive Control for Dynamic Resource Allocation," Mathematics of Operations Research, INFORMS, vol. 37(3), pages 501-525, August.
    8. Dan Zhang, 2011. "An Improved Dynamic Programming Decomposition Approach for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 13(1), pages 35-52, April.
    9. Alexander Erdelyi & Huseyin Topaloglu, 2010. "A Dynamic Programming Decomposition Method for Making Overbooking Decisions Over an Airline Network," INFORMS Journal on Computing, INFORMS, vol. 22(3), pages 443-456, August.
    10. Juan M. Chaneton & Gustavo Vulcano, 2011. "Computing Bid Prices for Revenue Management Under Customer Choice Behavior," Manufacturing & Service Operations Management, INFORMS, vol. 13(4), pages 452-470, October.
    11. Hübner, Alexander & Hense, Jonas & Dethlefs, Christian, 2022. "The revival of retail stores via omnichannel operations: A literature review and research framework," European Journal of Operational Research, Elsevier, vol. 302(3), pages 799-818.
    12. Chevalier, Philippe & Lamas, Alejandro & Lu, Liang & Mlinar, Tanja, 2015. "Revenue management for operations with urgent orders," European Journal of Operational Research, Elsevier, vol. 240(2), pages 476-487.
    13. Yuhang Ma & Paat Rusmevichientong & Mika Sumida & Huseyin Topaloglu, 2020. "An Approximation Algorithm for Network Revenue Management Under Nonstationary Arrivals," Operations Research, INFORMS, vol. 68(3), pages 834-855, May.
    14. Laumer, Simon & Barz, Christiane, 2023. "Reductions of non-separable approximate linear programs for network revenue management," European Journal of Operational Research, Elsevier, vol. 309(1), pages 252-270.
    15. Georgia Perakis & Guillaume Roels, 2010. "Robust Controls for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 12(1), pages 56-76, November.
    16. L. F. Escudero & J. F. Monge & D. Romero Morales & J. Wang, 2013. "Expected Future Value Decomposition Based Bid Price Generation for Large-Scale Network Revenue Management," Transportation Science, INFORMS, vol. 47(2), pages 181-197, May.
    17. Mahar, Stephen & Bretthauer, Kurt M. & Venkataramanan, M.A., 2009. "The value of virtual pooling in dual sales channel supply chains," European Journal of Operational Research, Elsevier, vol. 192(2), pages 561-575, January.
    18. Sebastian Koch & Jochen Gönsch & Michael Hassler & Robert Klein, 2016. "Practical decision rules for risk-averse revenue management using simulation-based optimization," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(6), pages 468-487, December.
    19. Ş. İlker Birbil & J. B. G. Frenk & Joaquim A. S. Gromicho & Shuzhong Zhang, 2014. "A Network Airline Revenue Management Framework Based on Decomposition by Origins and Destinations," Transportation Science, INFORMS, vol. 48(3), pages 313-333, August.
    20. Nicolas Houy & François Le Grand, 2015. "The Monte Carlo first-come-first-served heuristic for network revenue management," Working Papers halshs-01155698, HAL.

    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:inm:orinte:v:49:y:2019:i:5:p:355-370. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.