國立虎尾科技大學 |

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

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Optimization of Stochastic Discrete Systems and Control on Complex Networks/ by Dmitrii Lozovanu, Stefan Pickl.
Reminder of title:	Computational Networks /
Author:	Lozovanu, Dmitrii.
other author:	Pickl, Stefan.
Description:	XIX, 400 p. 54 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Operations research. -
Online resource:	https://doi.org/10.1007/978-3-319-11833-8
ISBN:	9783319118338

Optimization of Stochastic Discrete Systems and Control on Complex Networks = Computational Networks /
Lozovanu, Dmitrii.

Optimization of Stochastic Discrete Systems and Control on Complex NetworksComputational Networks /[electronic resource] :by Dmitrii Lozovanu, Stefan Pickl. - 1st ed. 2015. - XIX, 400 p. 54 illus.online resource. - Advances in Computational Management Science,121388-4301 ;. - Advances in Computational Management Science,12.

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.

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.

ISBN: 9783319118338

Standard No.: 10.1007/978-3-319-11833-8doiSubjects--Topical Terms:

573517
Operations research.

LC Class. No.: HD30.23

Dewey Class. No.: 658.40301

Optimization of Stochastic Discrete Systems and Control on Complex Networks = Computational Networks /
LDR:03109nam a22004215i 4500 001 968938
003 DE-He213
005 20200919221012.0
007 cr nn 008mamaa
008 201211s2015 gw | s |||| 0|eng d
020 $a 9783319118338 $9 978-3-319-11833-8
024 7 $a 10.1007/978-3-319-11833-8 $2 doi
035 $a 978-3-319-11833-8
050 4 $a HD30.23
072 7 $a KJT $2 bicssc
072 7 $a BUS049000 $2 bisacsh
072 7 $a KJT $2 thema
072 7 $a KJMD $2 thema
082 0 4 $a 658.40301 $2 23
100 1 $a Lozovanu, Dmitrii. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1063871
245 1 0 $a Optimization of Stochastic Discrete Systems and Control on Complex Networks $h [electronic resource] : $b Computational Networks / $c by Dmitrii Lozovanu, Stefan Pickl.
250 $a 1st ed. 2015.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a XIX, 400 p. 54 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Advances in Computational Management Science, $x 1388-4301 ; $v 12
505 0 $a 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.
520 $a 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.
650 0 $a Operations research. $3 573517
650 0 $a Decision making. $3 528319
650 0 $a Mathematical optimization. $3 527675
650 0 $a Management science. $3 719678
650 0 $a Algorithms. $3 527865
650 1 4 $a Operations Research/Decision Theory. $3 669176
650 2 4 $a Optimization. $3 669174
650 2 4 $a Operations Research, Management Science. $3 785065
650 2 4 $a Discrete Optimization. $3 1019327
650 2 4 $a Algorithm Analysis and Problem Complexity. $3 593923
700 1 $a Pickl, Stefan. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 898218
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319118345
776 0 8 $i Printed edition: $z 9783319118321
776 0 8 $i Printed edition: $z 9783319358734
830 0 $a Advances in Computational Management Science, $x 1388-4301 ; $v 12 $3 1264539
856 4 0 $u https://doi.org/10.1007/978-3-319-11833-8
912 $a ZDB-2-SBE
912 $a ZDB-2-SXBM
950 $a Business and Economics (SpringerNature-11643)
950 $a Business and Management (R0) (SpringerNature-43719)