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Game Theory and Operations Research: Some Musings 50 Years Later

Author

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  • Martin Shubik

    (Yale School of Management, 56 Hillhouse Avenue, P.O. Box 208281, New Haven, Connecticut 06520)

Abstract

A discussion of the utilization of the methods of game theory in operations research is given together with a consideration of the future developments. The language and analogies provided by game theory are now broadly accepted. It is suggested that the deep successes of game theory have illuminated its limitations and have helped to open up investigations in computer science, behavioral economics and simulation where the limitations of intelligence and of data processing are taken into account.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Martin Shubik, 2002. "Game Theory and Operations Research: Some Musings 50 Years Later," Operations Research, INFORMS, vol. 50(1), pages 192-196, February.
    • Handle: RePEc:inm:oropre:v:50:y:2002:i:1:p:192-196
    DOI: 10.1287/opre.50.1.192.17789
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    References listed on IDEAS

    as
    1. Maurice W. Kirby, 2000. "Operations Research Trajectories: The Anglo-American Experience from the 1940s to the 1990s," Operations Research, INFORMS, vol. 48(5), pages 661-670, October.
    2. Harvey M. Wagner & Michael H. Rothkopf & Clayton J. Thomas & Hugh J. Miser, 1989. "OR Forum—The Next Decade in Operations Research: Comments on the Condor Report," Operations Research, INFORMS, vol. 37(4), pages 664-672, August.
    3. Martin Shubik, 1955. "The Uses of Game Theory in Management Science," Management Science, INFORMS, vol. 2(1), pages 40-54, October.
    4. Michael H. Rothkopf, 1994. "Ten Years of the OR Practice Section," Operations Research, INFORMS, vol. 42(1), pages 31-33, February.
    5. Hakold F. Smiddy & Lionel Naum, 1954. "Evolution of a "Science of Managing" in America," Management Science, INFORMS, vol. 1(1), pages 1-31, October.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

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    2. Nan Zhang & Heng Xu, 2024. "Fairness of Ratemaking for Catastrophe Insurance: Lessons from Machine Learning," Information Systems Research, INFORMS, vol. 35(2), pages 469-488, June.
    3. Wynn C Stirling & Teppo Felin, 2013. "Game Theory, Conditional Preferences, and Social Influence," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
    4. Theodore T. Allen & Olivia K. Hernand & Abdullah Alomair, 2020. "Optimal Off-line Experimentation for Games," Decision Analysis, INFORMS, vol. 17(4), pages 277-298, December.
    5. Ruttan, Vernon W., 2007. "Imperialism, Colonialism and Collaboration in the Social Sciences," Staff Papers 7356, University of Minnesota, Department of Applied Economics.
    6. Thomas Kamalakis & Georgia Dede & Christos Michalakelis & Mara Nikolaidou, 2024. "Game-theoretic analysis of competition between access service providers utilizing a Nash genetic algorithm," Operational Research, Springer, vol. 24(2), pages 1-30, June.
    7. Zhao, Rui & Zhou, Xiao & Han, Jiaojie & Liu, Chengliang, 2016. "For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 262-274.
    8. Toraubally, Waseem A., 2023. "Comparative advantage with many goods: New treatment and results," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1188-1201.
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    10. Ensthaler, Ludwig & Giebe, Thomas, 2014. "Bayesian optimal knapsack procurement," European Journal of Operational Research, Elsevier, vol. 234(3), pages 774-779.

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    More about this item

    Keywords

    Professional; comments on;

    JEL classification:

    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory

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