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Foundations of Dynamic Optimization

In: Mathematical Optimization and Economic Analysis

Author

Listed:
  • Mikuláš Luptáčik

    (WU Vienna University of Economics and Business, Department of Economics)

  • Klaus Prettner

    (WU Vienna University of Economics and Business, Department of Economics)

Abstract

Dynamic optimization models decisions over time, using either continuous or discrete formulations. This chapter introduces optimal control theory and dynamic programming, with an emphasis on economic applications such as consumption smoothing and investment. Concepts like the Hamiltonian and Pontryagin’s maximum principle (for dynamic optimization in continuous time) and Bellman equations and the Hamilton–Jacobi–Bellman approach (for dynamic optimization in discrete time) are introduced within an accessible and intuitive way. This chapter highlights how intertemporal trade-offs can be rigorously described, modeled and solved, providing a framework for the analysis of long-term policy and planning problems.

Suggested Citation

  • Mikuláš Luptáčik & Klaus Prettner, 2026. "Foundations of Dynamic Optimization," Springer Optimization and Its Applications, in: Mathematical Optimization and Economic Analysis, edition 0, chapter 10, pages 325-352, Springer.
    • Handle: RePEc:spr:spochp:978-1-0716-5076-9_10
    DOI: 10.1007/978-1-0716-5076-9_10
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