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Discrete time Pontryagin Principles with Infinite Horizon

Author

Listed:
  • Blot, J.
  • Chebbi, H.

Abstract

We establish necessary conditions of optimality for problems of optimal control Theory in the discrete time framework with infinite horizon. Our necessary conditions are in the form of Pontryagin principles. We treat smooth and partially nonsmooth settings, without concavity. A strong motivation to the study of such problems comes from Dynamical Macroeconomic Theory, and there exist also some motivations provided by Physics.

Suggested Citation

  • Blot, J. & Chebbi, H., 2000. "Discrete time Pontryagin Principles with Infinite Horizon," Papiers d'Economie Mathématique et Applications 2000.20, Université Panthéon-Sorbonne (Paris 1).
    • Handle: RePEc:fth:pariem:2000.20
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    Citations

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    Cited by:

    1. Naïla Hayek, 2011. "A Generalization of Mixed Problems with an Application to Multiobjective Optimal Control," Journal of Optimization Theory and Applications, Springer, vol. 150(3), pages 498-515, September.
    2. Bertrand Crettez & Naila Hayek, 2014. "Terrorists’ Eradication Versus Perpetual Terror War," Journal of Optimization Theory and Applications, Springer, vol. 160(2), pages 679-702, February.
    3. Vasilev, Aleksandar, 2015. "The welfare effect of flat income tax reform: the case of Bulgaria," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 53(3), pages 205-220.
    4. Joël Blot & Thoi-Nhan Ngo, 2017. "Lightenings of Assumptions for Pontryagin Principles in Infinite Horizon and Discrete Time," Journal of Optimization Theory and Applications, Springer, vol. 172(2), pages 351-368, February.

    More about this item

    Keywords

    MACROECONOMICS ; OPTIMISATION ; ECONOMIC THEORY;
    All these keywords.

    JEL classification:

    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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