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Optimization of Stochastic Discrete Systems and Control on Complex Networks Computational Networks

Lozovanu Dmitrii Pickl, Stefan
Innbundet / 2014 / Engelsk

Produktdetaljer

ISBN
9783319118321
Publisert
2014-12-09
Utgiver
Vendor
Springer International Publishing AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, UP, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet

Forfatter
Lozovanu Dmitrii
Pickl, Stefan

Om bidragsyterne

Prof. Dr. Stefan Pickl is professor for Operations Research at Universität der Bundeswehr in Munich. He studied mathematics, electrical engineering, and philosophy at TU Darmstadt and EPFL Lausanne 1987-93. Dipl.-Ing. '93, Doctorate 1998 with award. Assistant Professor at Cologne University (Dr. habil. 2005; venia legendi ``Mathematics"). Visiting Professor at University of New Mexico (U.S.A.), University Graz (Austria), University of California at Berkeley. Visiting scientist at SANDIA, Los Alamos National Lab, Santa Fe Institute for Complex Systems and MIT. Associated with Centre for the Advanced Study of Algorithms (CASA, USA) and Center for Network Innovation and Experimentation (CENETIX, USA) , vice-chair of EURO group ``Experimental OR”, program for highly gifted pupils, research program``Intelligent Networks and Security Structures” (INESS), ``Critical Infrastructures and System Analyses" (CRISYS). International best paper awards ’03, ’05, '07. Foundation of COMTESSA (Competence Center for Operations Research, Strategic Planning Management, Safety & Security ALLIANCE).

Prof. Dr. Dmitrii Lozovanu received his PhD in mathematics  in 1980 from the Institute of Cybernetics of Academy of Sciences of Ukraine, Kiev. After the habilitation theses defense in 1991 he became professor in Computer Science. He is the head of department of Applied Mathematics at the Faculty of Mathematics and Computer Science of Moldova State University, Chisinau. His research interest

s are related to discrete optimization, game theory, optimal control and stochastic decision processes.

Optimization of Stochastic Discrete Systems and Control on Complex Networks Computational Networks

Lozovanu Dmitrii Pickl, Stefan
Innbundet / 2014 / Engelsk
Lozovanu Dmitrii Pickl, Stefan
Innbundet / 2014 / Engelsk
Nettpris:
1.213,-
Levering 7-20 dager
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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.
Les mer
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.
Les mer
​Discrete stochastic processes, numerical methods for Markov chains and polynomial time algorithms.- Stochastic optimal control problems and Markov decision processes with infinite time horizon.- A game-theoretical approach to Markov decision processes, stochastic positional games and multicriteria control models.- Dynamic programming algorithms for finite horizon control problems and Markov decision processes.
Les mer
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.
Les mer
“This book contributes to the systematization of the most relevant existing methods for these problems by introducing new algorithms for solving different classes of stochastic dynamic programming problems. … The mathematical and computational level of the book will enable students and practitioners to deepen their understanding of the topic. Numerous examples are included to illustrate the proposed algorithms and methods.” (Rosario Romera, Mathematical Reviews, July, 2015)
Les mer
Systematizes the most important existing methods of stochastic dynamic optimization Describes new algorithms for solving different classes of stochastic dynamic programming problems Presents methods to solve practical decision problems from diverse areas such as ecology, economics, engineering and communication systems Includes supplementary material: sn.pub/extras
Les mer

Relaterte produkter

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.
Les mer
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.
Les mer
​Discrete stochastic processes, numerical methods for Markov chains and polynomial time algorithms.- Stochastic optimal control problems and Markov decision processes with infinite time horizon.- A game-theoretical approach to Markov decision processes, stochastic positional games and multicriteria control models.- Dynamic programming algorithms for finite horizon control problems and Markov decision processes.
Les mer
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.
Les mer
“This book contributes to the systematization of the most relevant existing methods for these problems by introducing new algorithms for solving different classes of stochastic dynamic programming problems. … The mathematical and computational level of the book will enable students and practitioners to deepen their understanding of the topic. Numerous examples are included to illustrate the proposed algorithms and methods.” (Rosario Romera, Mathematical Reviews, July, 2015)
Les mer
Systematizes the most important existing methods of stochastic dynamic optimization Describes new algorithms for solving different classes of stochastic dynamic programming problems Presents methods to solve practical decision problems from diverse areas such as ecology, economics, engineering and communication systems Includes supplementary material: sn.pub/extras
Les mer

Produktdetaljer

ISBN
9783319118321
Publisert
2014-12-09
Utgiver
Vendor
Springer International Publishing AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, UP, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet

Forfatter
Lozovanu Dmitrii
Pickl, Stefan

Om bidragsyterne

Prof. Dr. Stefan Pickl is professor for Operations Research at Universität der Bundeswehr in Munich. He studied mathematics, electrical engineering, and philosophy at TU Darmstadt and EPFL Lausanne 1987-93. Dipl.-Ing. '93, Doctorate 1998 with award. Assistant Professor at Cologne University (Dr. habil. 2005; venia legendi ``Mathematics"). Visiting Professor at University of New Mexico (U.S.A.), University Graz (Austria), University of California at Berkeley. Visiting scientist at SANDIA, Los Alamos National Lab, Santa Fe Institute for Complex Systems and MIT. Associated with Centre for the Advanced Study of Algorithms (CASA, USA) and Center for Network Innovation and Experimentation (CENETIX, USA) , vice-chair of EURO group ``Experimental OR”, program for highly gifted pupils, research program``Intelligent Networks and Security Structures” (INESS), ``Critical Infrastructures and System Analyses" (CRISYS). International best paper awards ’03, ’05, '07. Foundation of COMTESSA (Competence Center for Operations Research, Strategic Planning Management, Safety & Security ALLIANCE).

Prof. Dr. Dmitrii Lozovanu received his PhD in mathematics  in 1980 from the Institute of Cybernetics of Academy of Sciences of Ukraine, Kiev. After the habilitation theses defense in 1991 he became professor in Computer Science. He is the head of department of Applied Mathematics at the Faculty of Mathematics and Computer Science of Moldova State University, Chisinau. His research interest

s are related to discrete optimization, game theory, optimal control and stochastic decision processes.

Relaterte produkter