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Autor(en): 
  • Stefan Pickl
  • Dmitrii Lozovanu
  • Optimization of Stochastic Discrete Systems and Control on Complex Networks: Computational Networks 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2016  
    Genre:  Wirtschaft / Recht 
     
    Algorithm Analysis and Problem Complexity / Algorithms / Algorithms & data structures / B / Business and Management / Decision Making / Discrete Optimization / Management & management techniques
    ISBN:  9783319358734 
    EAN-Code: 
    9783319358734 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #12 - Advances in Computational Management Science  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  646 gr 
    Seiten:  400 
    Illustration:  XIX, 400 p. 54 illus., schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors' new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book's final chapter is devoted to finite horizon stochastic control problems and Markov decision processes. The algorithms developed represent a valuable contribution to the important field of computational network theory.

      



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