IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v55y2008i8p800-810.html
   My bibliography  Save this article

Optimizing the US Navy's combat logistics force

Author

Listed:
  • Gerald G. Brown
  • W. Matthew Carlyle

Abstract

We study how changes to the composition and employment of the US Navy combat logistic force (CLF) influence our ability to supply our navy worldwide. The CLF consists of about 30 special transport ships that carry ship and aircraft fuel, ordnance, dry stores, and food, and deliver these to client combatant ships underway, making it possible for our naval forces to operate at sea for extended periods. We have modeled CLF operations to evaluate a number of transforming initiatives that simplify its operation while supporting an even larger number of client ships for a greater variety of missions. Our input is an employment schedule for navy battle groups of ships operating worldwide, extending over a planning horizon of 90–180 days. We show how we use optimization to advise how to sustain these ships. We have used this model to evaluate new CLF ship designs, advise what number of ships in a new ship class would be needed, test concepts for forward at‐sea logistics bases in lieu of conventional ports, demonstrate the effects of changes to operating policy, and generally try to show whether and how the CLF can support planned naval operations. Published 2008 Wiley Periodicals, Inc. Naval Research Logistics 2008

Suggested Citation

  • Gerald G. Brown & W. Matthew Carlyle, 2008. "Optimizing the US Navy's combat logistics force," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(8), pages 800-810, December.
  • Handle: RePEc:wly:navres:v:55:y:2008:i:8:p:800-810
    DOI: 10.1002/nav.20318
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.20318
    Download Restriction: no

    File URL: https://libkey.io/10.1002/nav.20318?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. Gerald G. Brown & Glenn W. Graves & David Ronen, 1987. "Scheduling Ocean Transportation of Crude Oil," Management Science, INFORMS, vol. 33(3), pages 335-346, March.
    2. G. B. Dantzig & D. R. Fulkerson, 1954. "Minimizing the number of tankers to meet a fixed schedule," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 1(3), pages 217-222, September.
    3. Gerald G. Brown & Jeffrey E. Kline & Richard E. Rosenthal & Alan R. Washburn, 2007. "Steaming on Convex Hulls," Interfaces, INFORMS, vol. 37(4), pages 342-352, 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. Mofidi, Seyed Shahab & Pazour, Jennifer A. & Roy, Debjit, 2018. "Proactive vs. reactive order-fulfillment resource allocation for sea-based logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 66-84.
    2. Mohammad Marufuzzaman & Farjana Nur & Amy E. Bednar & Mark Cowan, 2020. "Enhancing Benders decomposition algorithm to solve a combat logistics problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 161-198, March.
    3. Gerald G. Brown & Walter C. DeGrange & Wilson L. Price & Anton A. Rowe, 2017. "Scheduling combat logistics force replenishments at sea for the US Navy," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(8), pages 677-693, 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. Wu, Lingxiao & Pan, Kai & Wang, Shuaian & Yang, Dong, 2018. "Bulk ship scheduling in industrial shipping with stochastic backhaul canvassing demand," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 117-136.
    2. Sun, Qinghe & Meng, Qiang & Chou, Mabel C., 2021. "Optimizing voyage charterparty (VCP) arrangement: Laytime negotiation and operations coordination," European Journal of Operational Research, Elsevier, vol. 291(1), pages 263-270.
    3. Michael R. Miller & Robert J. Alexander & Vincent A. Arbige & Robert F. Dell & Steven R. Kremer & Brian P. McClune & Jane E. Oppenlander & Joshua P. Tomlin, 2017. "Optimal Allocation of Students to Naval Nuclear-Power Training Units," Interfaces, INFORMS, vol. 47(4), pages 320-335, August.
    4. Hennig, F. & Nygreen, B. & Christiansen, M. & Fagerholt, K. & Furman, K.C. & Song, J. & Kocis, G.R. & Warrick, P.H., 2012. "Maritime crude oil transportation – A split pickup and split delivery problem," European Journal of Operational Research, Elsevier, vol. 218(3), pages 764-774.
    5. Thomas Buckley Imhoff & Savvas Gkantonas & Epaminondas Mastorakos, 2021. "Analysing the Performance of Ammonia Powertrains in the Marine Environment," Energies, MDPI, vol. 14(21), pages 1-41, November.
    6. Ricardo Gatica & Pablo Miranda, 2011. "Special Issue on Latin-American Research: A Time Based Discretization Approach for Ship Routing and Scheduling with Variable Speed," Networks and Spatial Economics, Springer, vol. 11(3), pages 465-485, September.
    7. D Ronen, 2011. "The effect of oil price on containership speed and fleet size," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 211-216, January.
    8. Fagerholt, Kjetil, 2001. "Ship scheduling with soft time windows: An optimisation based approach," European Journal of Operational Research, Elsevier, vol. 131(3), pages 559-571, June.
    9. Gerald G. Brown & Walter C. DeGrange & Robert F. Dell & Ronald D. Fricker, 2015. "ASP, Art and Science of Practice: Educating Military Operations Research Practitioners," Interfaces, INFORMS, vol. 45(2), pages 175-186, April.
    10. Al-Khayyal, Faiz & Hwang, Seung-June, 2007. "Inventory constrained maritime routing and scheduling for multi-commodity liquid bulk, Part I: Applications and model," European Journal of Operational Research, Elsevier, vol. 176(1), pages 106-130, January.
    11. Gerald G. Brown & Richard E. Rosenthal, 2008. "Optimization Tradecraft: Hard-Won Insights from Real-World Decision Support," Interfaces, INFORMS, vol. 38(5), pages 356-366, October.
    12. Amir Alizadeh & Wayne Talley, 2011. "Microeconomic determinants of dry bulk shipping freight rates and contract times," Transportation, Springer, vol. 38(3), pages 561-579, May.
    13. Shih, Li-Hsing, 1997. "Planning of fuel coal imports using a mixed integer programming method," International Journal of Production Economics, Elsevier, vol. 51(3), pages 243-249, September.
    14. Geursen, Izaak L. & Santos, Bruno F. & Yorke-Smith, Neil, 2023. "Fleet planning under demand and fuel price uncertainty using actor–critic reinforcement learning," Journal of Air Transport Management, Elsevier, vol. 109(C).
    15. Yim, Seho & Hong, Sung-Pil & Park, Myoung-Ju & Chung, Yerim, 2022. "Inverse interval scheduling via reduction on a single machine," European Journal of Operational Research, Elsevier, vol. 303(2), pages 541-549.
    16. Ozelkan, Ertunga C. & D'Ambrosio, Alfred & Teng, S. Gary, 2008. "Optimizing liquefied natural gas terminal design for effective supply-chain operations," International Journal of Production Economics, Elsevier, vol. 111(2), pages 529-542, February.
    17. Stern, Helman I. & Gertsbakh, Ilya B., 2019. "Using deficit functions for aircraft fleet routing," Operations Research Perspectives, Elsevier, vol. 6(C).
    18. Alexandra M. Newman & Richard E. Rosenthal & Javier Salmerón & Gerald G. Brown & Wilson Price & Anton Rowe & Charles F. Fennemore & Robert L. Taft, 2011. "Optimizing assignment of Tomahawk cruise missile missions to firing units," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(3), pages 281-294, April.
    19. Antoon W.J. Kolen & Jan Karel Lenstra & Christos H. Papadimitriou & Frits C.R. Spieksma, 2007. "Interval scheduling: A survey," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(5), pages 530-543, August.
    20. Bilgen, Bilge & Ozkarahan, Irem, 2007. "A mixed-integer linear programming model for bulk grain blending and shipping," International Journal of Production Economics, Elsevier, vol. 107(2), pages 555-571, June.

    More about this item

    Statistics

    Access and download statistics

    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:wly:navres:v:55:y:2008:i:8:p:800-810. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6750 .

    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.