IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v304y2021i1d10.1007_s10479-021-04193-y.html
   My bibliography  Save this article

Managing mobile production-inventory systems influenced by a modulation process

Author

Listed:
  • Satya S. Malladi

    (Kantar Analytics Practice)

  • Alan L. Erera

    (Georgia Institute of Technology)

  • Chelsea C. White

    (Georgia Institute of Technology)

Abstract

The objective of this paper is to investigate the potential added value of being able to relocate production capacity, relative to fixed production capacity, in a network of multiple, geographically distributed manufacturing sites. There is a growing number of examples of production capacity that can be geographically relocated with a modest amount of effort; e.g., 3D printers, bioreactors for cell and gene manufacturing, and modular units for pharmaceutical intermediates. Such a capability shows promise for enabling the fast fulfillment of a distributed network with a reduction in the total inventory and total production capacity of a distributed network with fixed production capacity without sacrificing customer service levels or total system resilience. Allowing also for transshipment, we model a production-inventory system with L production sites and Y units of relocatable production capacity, develop efficient and effective heuristic solution methods for dynamic relocation and multi-location inventory control, and analyze the potential added value and implementation challenges of being able to relocate production capacity. We describe the (L, Y) problem as a problem of sequential decision making under uncertainty to determine transshipment, mobile production capacity relocation, and replenishment decisions at each decision epoch. To enhance model realism, we use a partially observed stochastic process, the modulation process, to model the exogenous and partially observable forces (e.g., the macro-economy) that affect demand. We then model the (L, Y) problem as a partially observed Markov decision process. Due to the considerable computational challenges of solving this model exactly, we propose two efficient, high quality heuristics. We show for an instance set with five locations that production capacity mobility and transshipment, relative to the fixed production capacity case, can improve systems performance by as much as 41% on average over the no-flexibility case and that production capacity mobility can yield as much as 10% more savings compared to when only transshipment is permitted.

Suggested Citation

  • Satya S. Malladi & Alan L. Erera & Chelsea C. White, 2021. "Managing mobile production-inventory systems influenced by a modulation process," Annals of Operations Research, Springer, vol. 304(1), pages 299-330, September.
  • Handle: RePEc:spr:annopr:v:304:y:2021:i:1:d:10.1007_s10479-021-04193-y
    DOI: 10.1007/s10479-021-04193-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-021-04193-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-021-04193-y?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
    ---><---

    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. William S. Lovejoy, 1991. "Computationally Feasible Bounds for Partially Observed Markov Decision Processes," Operations Research, INFORMS, vol. 39(1), pages 162-175, February.
    2. Panagiotis Kouvelis & Genaro J. Gutierrez, 1997. "The Newsvendor Problem in a Global Market: Optimal Centralized and Decentralized Control Policies for a Two-Market Stochastic Inventory System," Management Science, INFORMS, vol. 43(5), pages 571-585, May.
    3. Uday S. Karmarkar, 1979. "Convex/stochastic programming and multilocation inventory problems," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 26(1), pages 1-19, March.
    4. Fernando Bernstein & Awi Federgruen, 2005. "Decentralized Supply Chains with Competing Retailers Under Demand Uncertainty," Management Science, INFORMS, vol. 51(1), pages 18-29, January.
    5. Nils Rudi & Sandeep Kapur & David F. Pyke, 2001. "A Two-Location Inventory Model with Transshipment and Local Decision Making," Management Science, INFORMS, vol. 47(12), pages 1668-1680, December.
    6. Richard D. Smallwood & Edward J. Sondik, 1973. "The Optimal Control of Partially Observable Markov Processes over a Finite Horizon," Operations Research, INFORMS, vol. 21(5), pages 1071-1088, October.
    7. William C. Jordan & Stephen C. Graves, 1995. "Principles on the Benefits of Manufacturing Process Flexibility," Management Science, INFORMS, vol. 41(4), pages 577-594, April.
    8. Uday S. Karmarkar, 1987. "The Multilocation Multiperiod Inventory Problem: Bounds and Approximations," Management Science, INFORMS, vol. 33(1), pages 86-94, January.
    9. A. Federgruen & P. Zipkin, 1986. "An Inventory Model with Limited Production Capacity and Uncertain Demands II. The Discounted-Cost Criterion," Mathematics of Operations Research, INFORMS, vol. 11(2), pages 208-215, May.
    10. Edward J. Sondik, 1978. "The Optimal Control of Partially Observable Markov Processes over the Infinite Horizon: Discounted Costs," Operations Research, INFORMS, vol. 26(2), pages 282-304, April.
    11. Wang Chi Cheung & David Simchi-Levi, 2019. "Sampling-Based Approximation Schemes for Capacitated Stochastic Inventory Control Models," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 668-692, May.
    12. Fernando Bernstein & Gregory A. DeCroix, 2006. "Inventory Policies in a Decentralized Assembly System," Operations Research, INFORMS, vol. 54(2), pages 324-336, April.
    13. Uday S. Karmarkar, 1981. "The Multiperiod Multilocation Inventory Problem," Operations Research, INFORMS, vol. 29(2), pages 215-228, April.
    14. Jiaming Qiu & Thomas Sharkey, 2013. "Integrated dynamic single-facility location and inventory planning problems," IISE Transactions, Taylor & Francis Journals, vol. 45(8), pages 883-895.
    15. Satya S. Malladi & Alan L. Erera & Chelsea C. White, 2020. "A dynamic mobile production capacity and inventory control problem," IISE Transactions, Taylor & Francis Journals, vol. 52(8), pages 926-943, August.
    16. Apostolos N. Burnetas & Michael N. Katehakis, 1997. "Optimal Adaptive Policies for Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 22(1), pages 222-255, February.
    17. Kwan Eng Wee & Maqbool Dada, 2005. "Optimal Policies for Transshipping Inventory in a Retail Network," Management Science, INFORMS, vol. 51(10), pages 1519-1533, October.
    18. Herer, Yale T. & Tzur, Michal & Yucesan, Enver, 2002. "Transshipments: An emerging inventory recourse to achieve supply chain leagility," International Journal of Production Economics, Elsevier, vol. 80(3), pages 201-212, December.
    19. Sanjay Dominik Jena & Jean-François Cordeau & Bernard Gendron, 2015. "Dynamic Facility Location with Generalized Modular Capacities," Transportation Science, INFORMS, vol. 49(3), pages 484-499, August.
    20. Nicola Secomandi, 2001. "A Rollout Policy for the Vehicle Routing Problem with Stochastic Demands," Operations Research, INFORMS, vol. 49(5), pages 796-802, October.
    21. Gregory A. Godfrey & Warren B. Powell, 2001. "An Adaptive, Distribution-Free Algorithm for the Newsvendor Problem with Censored Demands, with Applications to Inventory and Distribution," Management Science, INFORMS, vol. 47(8), pages 1101-1112, August.
    22. A. Federgruen & P. Zipkin, 1986. "An Inventory Model with Limited Production Capacity and Uncertain Demands I. The Average-Cost Criterion," Mathematics of Operations Research, INFORMS, vol. 11(2), pages 193-207, May.
    23. Goodson, Justin C. & Thomas, Barrett W. & Ohlmann, Jeffrey W., 2017. "A rollout algorithm framework for heuristic solutions to finite-horizon stochastic dynamic programs," European Journal of Operational Research, Elsevier, vol. 258(1), pages 216-229.
    24. Russell Halper & S. Raghavan, 2011. "The Mobile Facility Routing Problem," Transportation Science, INFORMS, vol. 45(3), pages 413-434, August.
    25. Ilya O. Ryzhov & Warren B. Powell & Peter I. Frazier, 2012. "The Knowledge Gradient Algorithm for a General Class of Online Learning Problems," Operations Research, INFORMS, vol. 60(1), pages 180-195, February.
    26. Sven Axsäter & Johan Marklund & Edward A. Silver, 2002. "Heuristic Methods for Centralized Control of One-Warehouse, N-Retailer Inventory Systems," Manufacturing & Service Operations Management, INFORMS, vol. 4(1), pages 75-97, October.
    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. Satya S. Malladi & Alan L. Erera & Chelsea C. White, 2023. "Inventory control with modulated demand and a partially observed modulation process," Annals of Operations Research, Springer, vol. 321(1), pages 343-369, February.

    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. Junxuan Li & Chelsea C. White, 2023. "Capacity planning in a decentralized autologous cell therapy manufacturing network for low-cost resilience," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 295-319, June.
    2. Jian Yang & Zhaoqiong Qin, 2007. "Capacitated Production Control with Virtual Lateral Transshipments," Operations Research, INFORMS, vol. 55(6), pages 1104-1119, December.
    3. Xinxin Hu & Izak Duenyas & Roman Kapuscinski, 2008. "Optimal Joint Inventory and Transshipment Control Under Uncertain Capacity," Operations Research, INFORMS, vol. 56(4), pages 881-897, August.
    4. Satya S. Malladi & Alan L. Erera & Chelsea C. White, 2023. "Inventory control with modulated demand and a partially observed modulation process," Annals of Operations Research, Springer, vol. 321(1), pages 343-369, February.
    5. Yale T. Herer & Michal Tzur, 2001. "The dynamic transshipment problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(5), pages 386-408, August.
    6. Hao Zhang, 2010. "Partially Observable Markov Decision Processes: A Geometric Technique and Analysis," Operations Research, INFORMS, vol. 58(1), pages 214-228, February.
    7. Tiacci, Lorenzo & Saetta, Stefano, 2011. "Reducing the mean supply delay of spare parts using lateral transshipments policies," International Journal of Production Economics, Elsevier, vol. 133(1), pages 182-191, September.
    8. Ying Rong & Lawrence V. Snyder & Yang Sun, 2010. "Inventory sharing under decentralized preventive transshipments," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(6), pages 540-562, September.
    9. Dong, Yan & Xu, Kefeng & Evers, Philip T., 2012. "Transshipment incentive contracts in a multi-level supply chain," European Journal of Operational Research, Elsevier, vol. 223(2), pages 430-440.
    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. Williams, Byron K., 2011. "Resolving structural uncertainty in natural resources management using POMDP approaches," Ecological Modelling, Elsevier, vol. 222(5), pages 1092-1102.
    12. Weidong Chen & Cong Shi & Izak Duenyas, 2020. "Optimal Learning Algorithms for Stochastic Inventory Systems with Random Capacities," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1624-1649, July.
    13. Shrutivandana Sharma & Hossein Abouee‐Mehrizi & Giorgio Sartor, 2020. "Inventory Management under Storage and Order Restrictions," Production and Operations Management, Production and Operations Management Society, vol. 29(1), pages 101-117, January.
    14. Elodie Adida & Georgia Perakis, 2014. "The effect of supplier capacity on the supply chain profit," Annals of Operations Research, Springer, vol. 223(1), pages 1-52, December.
    15. Tiacci, Lorenzo & Saetta, Stefano, 2011. "A heuristic for balancing the inventory level of different locations through lateral shipments," International Journal of Production Economics, Elsevier, vol. 131(1), pages 87-95, May.
    16. Jan A. Van Mieghem & Nils Rudi, 2002. "Newsvendor Networks: Inventory Management and Capacity Investment with Discretionary Activities," Manufacturing & Service Operations Management, INFORMS, vol. 4(4), pages 313-335, August.
    17. Lauren Xiaoyuan Lu & Jan A. Van Mieghem, 2009. "Multimarket Facility Network Design with Offshoring Applications," Manufacturing & Service Operations Management, INFORMS, vol. 11(1), pages 90-108, October.
    18. Sari, Kazim, 2010. "Exploring the impacts of radio frequency identification (RFID) technology on supply chain performance," European Journal of Operational Research, Elsevier, vol. 207(1), pages 174-183, November.
    19. James A. Rappold & John A. Muckstadt, 2000. "A computationally efficient approach for determining inventory levels in a capacitated multiechelon production‐distribution system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(5), pages 377-398, August.
    20. Y. Boulaksil & J. C. Fransoo & T. Tan, 2017. "Capacity reservation and utilization for a manufacturer with uncertain capacity and demand," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 689-709, July.

    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:spr:annopr:v:304:y:2021:i:1:d:10.1007_s10479-021-04193-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.