IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v107y2022ics0305048321001717.html
   My bibliography  Save this article

The Weapon Target Assignment Problem: Rational Inference of Adversary Target Utility Valuations from Observed Solutions

Author

Listed:
  • Hughes, Michael S.
  • Lunday, Brian J.

Abstract

Identifying an adversary’s strategic goals and values requires deliberate and unbiased analysis. This research is motivated by the premise that, if one observes an adversary’s actions or planned actions, it is possible to draw reasonable inferences about their values, thereby reducing misperceptions and informing better decisions. Within the context of the static weapon target assignment problem, this research develops and empirically compares alternative methods to rationalize an adversary’s value hierarchy over targets that informs their observed decisions. Such methods either identify the extreme points of a polytope within a unit simplex of relative target values that encompasses all possible relative target values based on a weak dominance criterion or a subset of points within the polytope. This research characterizes the solution methods’ practical tractability for use on larger-sized problems and their generalizability to other problems. Even for the superlative technique examined, testing illustrates the computationally challenging nature of identifying the defining polytope of relative target values, and the work concludes with suggestions for metaheuristic technique development.

Suggested Citation

  • Hughes, Michael S. & Lunday, Brian J., 2022. "The Weapon Target Assignment Problem: Rational Inference of Adversary Target Utility Valuations from Observed Solutions," Omega, Elsevier, vol. 107(C).
  • Handle: RePEc:eee:jomega:v:107:y:2022:i:c:s0305048321001717
    DOI: 10.1016/j.omega.2021.102562
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048321001717
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.omega.2021.102562?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. Ravindra K. Ahuja & James B. Orlin, 2001. "Inverse Optimization," Operations Research, INFORMS, vol. 49(5), pages 771-783, October.
    2. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    3. Pferschy, Ulrich & Nicosia, Gaia & Pacifici, Andrea & Schauer, Joachim, 2021. "On the Stackelberg knapsack game," European Journal of Operational Research, Elsevier, vol. 291(1), pages 18-31.
    4. Patrick Bajari & Han Hong & Stephen P. Ryan, 2010. "Identification and Estimation of a Discrete Game of Complete Information," Econometrica, Econometric Society, vol. 78(5), pages 1529-1568, September.
    5. G. G. denBroeder & R. E. Ellison & L. Emerling, 1959. "On Optimum Target Assignments," Operations Research, INFORMS, vol. 7(3), pages 322-326, June.
    6. Alan S. Manne, 1958. "A Target-Assignment Problem," Operations Research, INFORMS, vol. 6(3), pages 346-351, June.
    7. Paul R. Milgrom & Robert J. Weber, 1985. "Distributional Strategies for Games with Incomplete Information," Mathematics of Operations Research, INFORMS, vol. 10(4), pages 619-632, November.
    8. Wagner, R. Harrison, 1991. "Nuclear Deterrence, Counterforce Strategies, and the Incentive to Strike First," American Political Science Review, Cambridge University Press, vol. 85(3), pages 727-749, September.
    9. M. Hosein Zare & Oleg A. Prokopyev & Denis Sauré, 2020. "On Bilevel Optimization with Inexact Follower," Decision Analysis, INFORMS, vol. 17(1), pages 74-95, March.
    10. Nicholas T. Boardman & Brian J. Lunday & Matthew J. Robbins, 2017. "Heterogeneous surface-to-air missile defense battery location: a game theoretic approach," Journal of Heuristics, Springer, vol. 23(6), pages 417-447, December.
    11. John C. Harsanyi, 1967. "Games with Incomplete Information Played by "Bayesian" Players, I-III Part I. The Basic Model," Management Science, INFORMS, vol. 14(3), pages 159-182, November.
    12. Keith, Andrew & Ahner, Darryl, 2021. "Counterfactual regret minimization for integrated cyber and air defense resource allocation," European Journal of Operational Research, Elsevier, vol. 292(1), pages 95-107.
    13. P. T. Sokkalingam & Ravindra K. Ahuja & James B. Orlin, 1999. "Solving Inverse Spanning Tree Problems Through Network Flow Techniques," Operations Research, INFORMS, vol. 47(2), pages 291-298, April.
    14. Benoît Colson & Patrice Marcotte & Gilles Savard, 2007. "An overview of bilevel optimization," Annals of Operations Research, Springer, vol. 153(1), pages 235-256, September.
    15. Powell, Warren B., 2019. "A unified framework for stochastic optimization," European Journal of Operational Research, Elsevier, vol. 275(3), pages 795-821.
    16. Chan Y. Han & Brian J. Lunday & Matthew J. Robbins, 2016. "A Game Theoretic Model for the Optimal Location of Integrated Air Defense System Missile Batteries," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 405-416, August.
    17. Matthias Ehrgott, 2005. "Multicriteria Optimization," Springer Books, Springer, edition 0, number 978-3-540-27659-3, September.
    18. Bresnahan, Timothy F. & Reiss, Peter C., 1991. "Empirical models of discrete games," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 57-81.
    19. Varian, Hal R, 1982. "The Nonparametric Approach to Demand Analysis," Econometrica, Econometric Society, vol. 50(4), pages 945-973, July.
    20. Savelli, Iacopo & Morstyn, Thomas, 2021. "Electricity prices and tariffs to keep everyone happy: A framework for fixed and nodal prices coexistence in distribution grids with optimal tariffs for investment cost recovery," Omega, Elsevier, vol. 103(C).
    21. F. Lemus & K. H. David, 1963. "An Optimum Allocation of Different Weapons to a Target Complex," Operations Research, INFORMS, vol. 11(5), pages 787-794, October.
    22. Ketkov, Sergey S. & Prokopyev, Oleg A., 2020. "On greedy and strategic evaders in sequential interdiction settings with incomplete information," Omega, Elsevier, vol. 92(C).
    23. Cai Mao-Cheng & Yanjun Li, 1997. "Inverse Matroid Intersection Problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 45(2), pages 235-243, June.
    24. John C. Harsanyi, 1968. "Games with Incomplete Information Played by "Bayesian" Players Part II. Bayesian Equilibrium Points," Management Science, INFORMS, vol. 14(5), pages 320-334, January.
    25. MERTENS, Jean-François & ZAMIR, Shmuel, 1985. "Formulation of Bayesian analysis for games with incomplete information," LIDAM Reprints CORE 608, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    26. Ravindra K. Ahuja & Arvind Kumar & Krishna C. Jha & James B. Orlin, 2007. "Exact and Heuristic Algorithms for the Weapon-Target Assignment Problem," Operations Research, INFORMS, vol. 55(6), pages 1136-1146, December.
    27. Davis, Michael T. & Robbins, Matthew J. & Lunday, Brian J., 2017. "Approximate dynamic programming for missile defense interceptor fire control," European Journal of Operational Research, Elsevier, vol. 259(3), pages 873-886.
    28. Iacopo Savelli & Thomas Morstyn, 2020. "Electricity prices and tariffs to keep everyone happy: a framework for fixed and nodal prices coexistence in distribution grids with optimal tariffs for investment cost recovery," Papers 2001.04283, arXiv.org, revised Jun 2021.
    29. Lu, Yiping & Chen, Danny Z., 2021. "A new exact algorithm for the Weapon-Target Assignment problem," Omega, Elsevier, vol. 98(C).
    30. Jabarzare, Ziba & Zolfagharinia, Hossein & Najafi, Mehdi, 2020. "Dynamic interdiction networks with applications in illicit supply chains," Omega, Elsevier, vol. 96(C).
    31. Grimm, Veronika & Orlinskaya, Galina & Schewe, Lars & Schmidt, Martin & Zöttl, Gregor, 2021. "Optimal design of retailer-prosumer electricity tariffs using bilevel optimization," Omega, Elsevier, vol. 102(C).
    32. Alexander G. Kline & Darryl K. Ahner & Brian J. Lunday, 2020. "A heuristic and metaheuristic approach to the static weapon target assignment problem," Journal of Global Optimization, Springer, vol. 78(4), pages 791-812, December.
    33. Clemens Heuberger, 2004. "Inverse Combinatorial Optimization: A Survey on Problems, Methods, and Results," Journal of Combinatorial Optimization, Springer, vol. 8(3), pages 329-361, September.
    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. Alexandre Colaers Andersen & Konstantin Pavlikov & Túlio A. M. Toffolo, 2022. "Weapon-target assignment problem: exact and approximate solution algorithms," Annals of Operations Research, Springer, vol. 312(2), pages 581-606, May.
    2. Martin Meier & Burkhard Schipper, 2014. "Bayesian games with unawareness and unawareness perfection," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 56(2), pages 219-249, June.
    3. Chan Y. Han & Brian J. Lunday & Matthew J. Robbins, 2016. "A Game Theoretic Model for the Optimal Location of Integrated Air Defense System Missile Batteries," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 405-416, August.
    4. Daniel Lacker & Kavita Ramanan, 2019. "Rare Nash Equilibria and the Price of Anarchy in Large Static Games," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 400-422, May.
    5. Benjamin Patrick Evans & Mikhail Prokopenko, 2021. "Bounded rationality for relaxing best response and mutual consistency: The Quantal Hierarchy model of decision-making," Papers 2106.15844, arXiv.org, revised Mar 2023.
    6. Milchtaich, Igal, 2004. "Random-player games," Games and Economic Behavior, Elsevier, vol. 47(2), pages 353-388, May.
    7. Bennet Gebken & Sebastian Peitz, 2021. "Inverse multiobjective optimization: Inferring decision criteria from data," Journal of Global Optimization, Springer, vol. 80(1), pages 3-29, May.
    8. Sundström, David, 2016. "On Specification and Inference in the Econometrics of Public Procurement," Umeå Economic Studies 931, Umeå University, Department of Economics.
    9. Nguyen, Kien Trung & Hung, Nguyen Thanh, 2021. "The minmax regret inverse maximum weight problem," Applied Mathematics and Computation, Elsevier, vol. 407(C).
    10. Sundström, David, 2014. "It’s All in the Interval - An imperfect measurements approach to estimate bidders’ primitives in auctions," Umeå Economic Studies 899, Umeå University, Department of Economics, revised 17 Jun 2016.
    11. Juan Li & Bin Xin & Panos M. Pardalos & Jie Chen, 2021. "Solving bi-objective uncertain stochastic resource allocation problems by the CVaR-based risk measure and decomposition-based multi-objective evolutionary algorithms," Annals of Operations Research, Springer, vol. 296(1), pages 639-666, January.
    12. Alexander G. Kline & Darryl K. Ahner & Brian J. Lunday, 2019. "Real-time heuristic algorithms for the static weapon target assignment problem," Journal of Heuristics, Springer, vol. 25(3), pages 377-397, June.
    13. Vaughan, Jim & Doumen, Sjoerd C. & Kok, Koen, 2023. "Empowering tomorrow, controlling today: A multi-criteria assessment of distribution grid tariff designs," Applied Energy, Elsevier, vol. 341(C).
    14. Grant, Simon & Meneghel, Idione & Tourky, Rabee, 2016. "Savage games," Theoretical Economics, Econometric Society, vol. 11(2), May.
    15. Anissa Frini & Adel Guitouni & Abderrezak Benaskeur, 2017. "Solving Dynamic Multi-Criteria Resource-Target Allocation Problem Under Uncertainty: A Comparison of Decomposition and Myopic Approaches," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1465-1496, November.
    16. Paul L. E. Grieco, 2014. "Discrete games with flexible information structures: an application to local grocery markets," RAND Journal of Economics, RAND Corporation, vol. 45(2), pages 303-340, June.
    17. Arnaud Wolff, 2019. "On the Function of Beliefs in Strategic Social Interactions," Working Papers of BETA 2019-41, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    18. Xiao, Ruli, 2018. "Identification and estimation of incomplete information games with multiple equilibria," Journal of Econometrics, Elsevier, vol. 203(2), pages 328-343.
    19. Roger B. Myerson, 2004. "Comments on "Games with Incomplete Information Played by 'Bayesian' Players, I--III Harsanyi's Games with Incoplete Information"," Management Science, INFORMS, vol. 50(12_supple), pages 1818-1824, December.
    20. Meier, Martin, 2008. "Universal knowledge-belief structures," Games and Economic Behavior, Elsevier, vol. 62(1), pages 53-66, January.

    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:eee:jomega:v:107:y:2022:i:c:s0305048321001717. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.