IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v52y2005i7p682-700.html
   My bibliography  Save this article

Approximations and empirics for stochastic war equations

Author

Listed:
  • Kjell Hausken
  • John F. Moxnes

Abstract

The article develops a theorem which shows that the Lanchester linear war equations are not in general equal to the Kolmogorov linear war equations. The latter are time‐consuming to solve, and speed is important when a large number of simulations must be run to examine a large parameter space. Run times are provided, where time is a scarce factor in warfare. Four time efficient approximations are presented in the form of ordinary differential equations for the expected sizes and variances of each group, and the covariance, accounting for reinforcement and withdrawal of forces. The approximations are compared with “exact” Monte Carlo simulations and empirics from the WWII Ardennes campaign. The band spanned out by plus versus minus the incremented standard deviations captures some of the scatter in the empirics, but not all. With stochastically varying combat effectiveness coefficients, a substantial part of the scatter in the empirics is contained. The model is used to forecast possible futures. The implications of increasing the combat effectiveness coefficient governing the size of the Allied force, and injecting reinforcement to the German force during the Campaign, are evaluated, with variance assessments. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.

Suggested Citation

  • Kjell Hausken & John F. Moxnes, 2005. "Approximations and empirics for stochastic war equations," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(7), pages 682-700, October.
  • Handle: RePEc:wly:navres:v:52:y:2005:i:7:p:682-700
    DOI: 10.1002/nav.20105
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.20105
    Download Restriction: no

    File URL: https://libkey.io/10.1002/nav.20105?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. Patrick S. Chen & Peter Chu, 2001. "Applying Lanchester's linear law to model the Ardennes campaign," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(8), pages 653-661, December.
    2. Jerome Bracken, 1995. "Lanchester models of the ardennes campaign," Naval Research Logistics (NRL), John Wiley & Sons, vol. 42(4), pages 559-577, June.
    3. James G. Taylor & Gerald G. Brown, 1983. "Annihilation Prediction for Lanchester-Type Models of Modern Warfare," Operations Research, INFORMS, vol. 31(4), pages 752-771, August.
    4. Hausken, Kjell & Moxnes, John F., 2002. "Stochastic conditional and unconditional warfare," European Journal of Operational Research, Elsevier, vol. 140(1), pages 61-87, July.
    5. Ronald D. Fricker, 1998. "Attrition models of the Ardennes campaign," Naval Research Logistics (NRL), John Wiley & Sons, vol. 45(1), pages 1-22, 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. Kress, Moshe & Caulkins, Jonathan P. & Feichtinger, Gustav & Grass, Dieter & Seidl, Andrea, 2018. "Lanchester model for three-way combat," European Journal of Operational Research, Elsevier, vol. 264(1), pages 46-54.
    2. Anelí Bongers & José L. Torres, 2021. "A bottleneck combat model: an application to the Battle of Thermopylae," Operational Research, Springer, vol. 21(4), pages 2859-2877, December.
    3. Michael J Armstrong, 2014. "The salvo combat model with a sequential exchange of fire," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(10), pages 1593-1601, October.

    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. Ian R. Johnson & Niall J. MacKay, 2011. "Lanchester models and the battle of Britain," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(3), pages 210-222, April.
    2. Patrick S. Chen & Peter Chu, 2001. "Applying Lanchester's linear law to model the Ardennes campaign," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(8), pages 653-661, December.
    3. Anelí Bongers & José L. Torres, 2021. "A bottleneck combat model: an application to the Battle of Thermopylae," Operational Research, Springer, vol. 21(4), pages 2859-2877, December.
    4. Kress, Moshe & Caulkins, Jonathan P. & Feichtinger, Gustav & Grass, Dieter & Seidl, Andrea, 2018. "Lanchester model for three-way combat," European Journal of Operational Research, Elsevier, vol. 264(1), pages 46-54.
    5. M.P. Wiper & L.I. Pettit & K.D.S. Young, 2000. "Bayesian inference for a Lanchester type combat model," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(7), pages 541-558, October.
    6. C-Y Hung & G K Yang & P S Deng & T Tang & S-P Lan & P Chu, 2005. "Fitting Lanchester's square law to the Ardennes Campaign," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 942-946, August.
    7. Gerardo Minguela-Castro & Ruben Heradio & Carlos Cerrada, 2021. "Automated Support for Battle Operational–Strategic Decision-Making," Mathematics, MDPI, vol. 9(13), pages 1-15, June.
    8. Chad W. Seagren & Donald P. Gaver & Patricia A. Jacobs, 2019. "A stochastic air combat logistics decision model for Blue versus Red opposition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(8), pages 663-674, December.
    9. P.S. Sheeba & Debasish Ghose, 2008. "Optimal resource allocation and redistribution strategy in military conflicts with Lanchester square law attrition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(6), pages 581-591, September.
    10. Gregory Levitin & Kjell Hausken, 2010. "Resource Distribution in Multiple Attacks Against a Single Target," Risk Analysis, John Wiley & Sons, vol. 30(8), pages 1231-1239, August.
    11. Thomas W. Lucas & Turker Turkes, 2004. "Fitting Lanchester equations to the battles of Kursk and Ardennes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(1), pages 95-116, February.
    12. Stephen Biddle & Stephen Long, 2004. "Democracy and Military Effectiveness," Journal of Conflict Resolution, Peace Science Society (International), vol. 48(4), pages 525-546, August.
    13. Pettit, L. I. & Wiper, M. P. & Young, K. D. S., 2003. "Bayesian inference for some Lanchester combat laws," European Journal of Operational Research, Elsevier, vol. 148(1), pages 152-165, July.
    14. González, Eduardo & Villena, Marcelo, 2011. "Spatial Lanchester models," European Journal of Operational Research, Elsevier, vol. 210(3), pages 706-715, May.
    15. N. K. Jaiswal & Meena Kumari & B. S. Nagabhushana, 1995. "Optimal force mix in heterogeneous combat," Naval Research Logistics (NRL), John Wiley & Sons, vol. 42(6), pages 873-887, September.
    16. Chen, Hsi-Mei, 2007. "A non-linear inverse Lanchester square law problem in estimating the force-dependent attrition coefficients," European Journal of Operational Research, Elsevier, vol. 182(2), pages 911-922, October.
    17. Liu, Liwei & Yu, Jun & Guo, Zhi, 2006. "A kind of stochastic duel model for guerrilla war," European Journal of Operational Research, Elsevier, vol. 171(2), pages 430-438, June.
    18. Israel David, 1995. "Lanchester modeling and the biblical account of the battles of gibeah," Naval Research Logistics (NRL), John Wiley & Sons, vol. 42(4), pages 579-584, June.
    19. Ronald D. Fricker, 1998. "Attrition models of the Ardennes campaign," Naval Research Logistics (NRL), John Wiley & Sons, vol. 45(1), pages 1-22, February.
    20. Hausken, Kjell, 2019. "Governmental combat of the dynamics of multiple competing terrorist organizations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 166(C), pages 33-55.

    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:52:y:2005:i:7:p:682-700. 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.