IDEAS home Printed from https://ideas.repec.org/a/sae/joudef/v17y2020i1p99-116.html
   My bibliography  Save this article

Concept development for comprehensive operations support with modeling and simulation

Author

Listed:
  • Guido A Veldhuis
  • Nico M de Reus
  • Bas MJ Keijser

Abstract

Modern warfighting is not only conducted on the physical battlefield but also engages actors in the information and human landscapes. Across these landscapes many types of actors characterize a comprehensive environment. A commander and staff follow the operations planning process to translate a desired end-state to tactical effects and activities. Understanding the interactions between actors and factors that shape conflict and understanding how they can be influenced is highly challenging. Modeling and simulation methods that aim to describe and understand the behavior of complex systems can serve to structure information, derive problem insights, and identify effective interventions. These methods are not, however, common as part of operations planning and intelligence processes. This paper documents findings based on reported experiences from practice and based on concept development and experimentation workshops conducted with Dutch Armed Forces stakeholders. We identify eight challenges to the adoption of modeling and simulation in operations planning. We then present a decision support concept that incorporates several elements to counter the challenges identified in the form of a prototype approach called Comprehensive Operations Support with Modeling and Simulation (COSMOS). We describe the approach along several process steps, illustrated by examples from the concept development and experimentation case studies. We identify several avenues for future research assisting adoption of modeling and simulation in the operations planning process.

Suggested Citation

  • Guido A Veldhuis & Nico M de Reus & Bas MJ Keijser, 2020. "Concept development for comprehensive operations support with modeling and simulation," The Journal of Defense Modeling and Simulation, , vol. 17(1), pages 99-116, January.
    • Handle: RePEc:sae:joudef:v:17:y:2020:i:1:p:99-116
    DOI: 10.1177/1548512918814407
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1548512918814407
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1548512918814407?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. Steve Bankes, 1993. "Exploratory Modeling for Policy Analysis," Operations Research, INFORMS, vol. 41(3), pages 435-449, June.
    2. Erik Pruyt & Jan H. Kwakkel, 2014. "Radicalization under deep uncertainty: a multi-model exploration of activism, extremism, and terrorism," System Dynamics Review, System Dynamics Society, vol. 30(1-2), pages 1-28, January.
    3. Edward G. Anderson, 2011. "A dynamic model of counterinsurgency policy including the effects of intelligence, public security, popular support, and insurgent experience," System Dynamics Review, System Dynamics Society, vol. 27(2), pages 111-141, April.
    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. Patrick Steinmann & Koen van der Zwet & Bas Keijser, 2024. "Simulation‐based generation and analysis of multidimensional future scenarios with time series clustering," Futures & Foresight Science, John Wiley & Sons, vol. 6(4), 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. Auping, Willem L. & Pruyt, Erik & de Jong, Sijbren & Kwakkel, Jan H., 2016. "The geopolitical impact of the shale revolution: Exploring consequences on energy prices and rentier states," Energy Policy, Elsevier, vol. 98(C), pages 390-399.
    2. Erik Pruyt & Jan H. Kwakkel, 2014. "Radicalization under deep uncertainty: a multi-model exploration of activism, extremism, and terrorism," System Dynamics Review, System Dynamics Society, vol. 30(1-2), pages 1-28, January.
    3. Hidayatno, Akhmad & Jafino, Bramka Arga & Setiawan, Andri D. & Purwanto, Widodo Wahyu, 2020. "When and why does transition fail? A model-based identification of adoption barriers and policy vulnerabilities for transition to natural gas vehicles," Energy Policy, Elsevier, vol. 138(C).
    4. Erik Pruyt & Tushith Islam, 2015. "On generating and exploring the behavior space of complex models," System Dynamics Review, System Dynamics Society, vol. 31(4), pages 220-249, October.
    5. Erik Pruyt & Willem L. Auping & Jan H. Kwakkel, 2015. "Ebola in West Africa: Model-Based Exploration of Social Psychological Effects and Interventions," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(1), pages 2-14, January.
    6. Edward G. Anderson & David R. Keith & Jose Lopez, 2023. "Opportunities for system dynamics research in operations management for public policy," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1895-1920, June.
    7. Steinmann, Patrick & Auping, Willem L. & Kwakkel, Jan H., 2020. "Behavior-based scenario discovery using time series clustering," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    8. Jan H. Kwakkel & Erik Pruyt, 2015. "Using System Dynamics for Grand Challenges: The ESDMA Approach," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(3), pages 358-375, May.
    9. Evelina Trutnevyte & Céline Guivarch & Robert Lempert & Neil Strachan, 2016. "Reinvigorating the scenario technique to expand uncertainty consideration," Climatic Change, Springer, vol. 135(3), pages 373-379, April.
    10. Timothy Wojan & Anil Rupasingha, 2001. "Crisis as Opportunity: Local Context, Adaptive Agents and the Possibilities of Rural Development," Regional Studies, Taylor & Francis Journals, vol. 35(2), pages 141-152.
    11. Seyed Ahmad Reza Mir Mohammadi Kooshknow & Rob den Exter & Franco Ruzzenenti, 2020. "An Exploratory Agent-Based Modeling Analysis Approach to Test Business Models for Electricity Storage," Energies, MDPI, vol. 13(7), pages 1-14, April.
    12. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    13. Hackney, Jeremy & Marchal, Fabrice, 2011. "A coupled multi-agent microsimulation of social interactions and transportation behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 296-309, May.
    14. Babak Heydari & Michael J. Pennock, 2018. "Guiding the behavior of sociotechnical systems: The role of agent‐based modeling," Systems Engineering, John Wiley & Sons, vol. 21(3), pages 210-226, May.
    15. Subhadeep & Mukhopadhyay, 2022. "Modelplasticity and Abductive Decision Making," Papers 2203.03040, arXiv.org, revised Mar 2023.
    16. Shu-Heng Chen & Connie Houning Wang & Weikai Chen, 2017. "Matching Impacts of School Admission Mechanisms: An Agent-Based Approach," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(2), pages 217-241, March.
    17. Marchau, Vincent & Walker, Warren & van Duin, Ron, 2008. "An adaptive approach to implementing innovative urban transport solutions," Transport Policy, Elsevier, vol. 15(6), pages 405-412, November.
    18. B. Gersonius & J. Rijke & R. Ashley & P. Bloemen & E. Kelder & C. Zevenbergen, 2016. "Adaptive Delta Management for flood risk and resilience in Dordrecht, The Netherlands," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(2), pages 201-216, June.
    19. repec:osf:socarx:nwxae_v1 is not listed on IDEAS
    20. Keller, Klaus & Miltich, Louise I. & Robinson, Alexander & Tol, Richard S.J., 2007. "How Overconfident are Current Projections of Anthropogenic Carbon Dioxide Emissions?," Climate Change Modelling and Policy Working Papers 9321, Fondazione Eni Enrico Mattei (FEEM).
    21. Julie E. Shortridge & Seth D. Guikema, 2016. "Scenario Discovery with Multiple Criteria: An Evaluation of the Robust Decision‐Making Framework for Climate Change Adaptation," Risk Analysis, John Wiley & Sons, vol. 36(12), pages 2298-2312, December.

    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:sae:joudef:v:17:y:2020:i:1:p:99-116. 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: SAGE Publications (email available below). General contact details of provider: .

    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.