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Literature Review

In: Dynamic and Stochastic Multi-Project Planning

Author

Listed:
  • Philipp Melchiors

    (Technische Universität München)

Abstract

Dynamic programming is a general technique for solving sequential problems. The first comprehensive books on the topic have been written by Bellman [13] and Howard [62]. The most important methodologies for determining an optimal policy for a Markov decision process (MDP) are backward induction, value iteration (VI), policy iteration (PI) and linear programming. As MDPs are in discrete time where transitions have the same deterministic durations many results and methodologies, such as VI, cannot be directly applied to continuous-time Markov decision processes with exponentially distributed transition times.

Suggested Citation

  • Philipp Melchiors, 2015. "Literature Review," Lecture Notes in Economics and Mathematical Systems, in: Dynamic and Stochastic Multi-Project Planning, edition 127, chapter 0, pages 19-28, Springer.
    • Handle: RePEc:spr:lnechp:978-3-319-04540-5_3
    DOI: 10.1007/978-3-319-04540-5_3
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