IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i13p1534-d585748.html

Automated Support for Battle Operational–Strategic Decision-Making

Author

Listed:
  • Gerardo Minguela-Castro

    (Department of Computer Systems and Software Engineering, Universidad Nacional de Educacion a Distancia (UNED), 28040 Madrid, Spain)

  • Ruben Heradio

    (Department of Computer Systems and Software Engineering, Universidad Nacional de Educacion a Distancia (UNED), 28040 Madrid, Spain)

  • Carlos Cerrada

    (Department of Computer Systems and Software Engineering, Universidad Nacional de Educacion a Distancia (UNED), 28040 Madrid, Spain)

Abstract

Battle casualties are the subject of study in military operations research, which applies mathematical models to quantify the probability of victory vs. loss. In particular, different approaches have been proposed to model the course of battles. However, none of them provide adequate decision-making support for high-level command. To overcome this situation, this paper presents an innovative high-level decision-making model, which uses an adaptive and predictive control architecture. The paper reports empirical evidence supporting our model by considering one of the greatest battles of World War II: the Battle of Crete.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:13:p:1534-:d:585748
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/13/1534/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/13/1534/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Duffey, Romney B, 2017. "Dynamic theory of losses in wars and conflicts," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1013-1027.
    2. 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.
    3. Xavier Rubio-Campillo, 2016. "Model Selection in Historical Research Using Approximate Bayesian Computation," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-18, January.
    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. Jerome Bracken, 1995. "Lanchester models of the ardennes campaign," Naval Research Logistics (NRL), John Wiley & Sons, vol. 42(4), pages 559-577, June.
    6. Robert L. Helmbold, 1965. "Letter to the Editor—A Modification of Lanchester's Equations," Operations Research, INFORMS, vol. 13(5), pages 857-859, October.
    7. S. J. Deitchman, 1962. "A Lanchester Model of Guerrilla Warfare," Operations Research, INFORMS, vol. 10(6), pages 818-827, December.
    8. Donghyun Kim & Hyungil Moon & Donghyun Park & Hayong Shin, 2017. "An efficient approximate solution for stochastic Lanchester models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1470-1481, November.
    9. 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)

    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. 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.
    2. 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.
    3. Moshe Kress, 2020. "Lanchester Models for Irregular Warfare," Mathematics, MDPI, vol. 8(5), pages 1-14, May.
    4. 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.
    5. Vikram Mittal, 2026. "Estimating attrition coefficients for the Lanchester equations from small-unit combat models," The Journal of Defense Modeling and Simulation, , vol. 23(2), pages 193-205, April.
    6. Guillaume Vandenbroucke, 2025. "On The Economic Mechanics Of Warfare," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 66(2), pages 491-526, May.
    7. 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.
    8. 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.
    9. Adam T Biggs & Joseph A Hamilton & Rachel R Markwald, 2025. "Challenges of incorporating wounded personnel into small arms combat simulations," The Journal of Defense Modeling and Simulation, , vol. 22(2), pages 207-214, April.
    10. Adam T Biggs & Joseph A Hamilton & Rachel R Markwald, 2025. "Identifying appropriate scenario termination rules for squad-level simulations of warfighter lethality," The Journal of Defense Modeling and Simulation, , vol. 22(4), pages 521-528, October.
    11. N J MacKay, 2009. "Lanchester models for mixed forces with semi-dynamical target allocation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(10), pages 1421-1427, October.
    12. Sergey Salishev, 2025. "The Narrow Corridor of Stable Solutions in an Extended Osipov--Lanchester Model with Constant Total Population," Papers 2512.18515, arXiv.org.
    13. 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.
    14. 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.
    15. 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.
    16. Timothy A. McLennan-Smith & Alexander C. Kalloniatis & Zlatko Jovanoski & Harvinder S. Sidhu & Dale O. Roberts & Simon Watt & Isaac N. Towers, 2021. "A Mathematical Model of Humanitarian Aid Agencies in Attritional Conflict Environments," Operations Research, INFORMS, vol. 69(6), pages 1696-1714, November.
    17. Li, Meixuan Jade & Zhu, Cheng & Zhu, Xianqiang & Tse, Chi K., 2026. "Competitiveness of competing complex systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 682(C).
    18. 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.
    19. Michael P. Atkinson & Moshe Kress & Niall J. MacKay, 2021. "Targeting, Deployment, and Loss-Tolerance in Lanchester Engagements," Operations Research, INFORMS, vol. 69(1), pages 71-81, January.
    20. 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.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:gam:jmathe:v:9:y:2021:i:13:p:1534-:d:585748. 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: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.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.