Applied Probability Models with Optimization Applications – Sheldon M. Ross – 2nd Edition

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Concise advanced-level introduction to stochastic processes that frequently arise in applied probability. Largely self-contained text covers Poisson process, renewal theory, Markov chains, inventory theory, Brownian motion and continuous time optimization models, much more. Problems and references at chapter ends. “Excellent introduction.”

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  • 1. Introduction to stochastic processes
    2. The poisson rpcess
    3. Renewal theory
    4. Markov chains
    5. "semi-markov, markov renewal and regernerative processes"
    6. Markov decision processes
    7. Semi-markov decision processes
    8. Inventory theory
    9. Brownian motion and continuous time optimization models

    Appendices
    Index
  • Citation

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