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Stochastic Simulation Optimization for Discrete Event Systems: Perturbation Analysis, Ordinal Optimization and Beyond, Chen Chun-Hung, Jia Qing-Shan, Lee Loo Hay


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Склад Америка: 210 шт.  
При оформлении заказа до: 2025-08-04
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Автор: Chen Chun-Hung, Jia Qing-Shan, Lee Loo Hay
Название:  Stochastic Simulation Optimization for Discrete Event Systems: Perturbation Analysis, Ordinal Optimization and Beyond
ISBN: 9789814513005
Издательство: World Scientific Publishing
Классификация:

ISBN-10: 9814513008
Обложка/Формат: Hardback
Страницы: 276
Вес: 0.52 кг.
Дата издания: 28.08.2013
Серия: Mathematics
Язык: English
Иллюстрации: Black & white illustrations, figures
Размер: 231 x 155 x 20
Читательская аудитория: Postgraduate, research & scholarly
Ключевые слова: Optimization, MATHEMATICS / Optimization,MATHEMATICS / Probability & Statistics / Stochastic,TECHNOLOGY & ENGINEERING / Industrial Design / General
Подзаголовок: Perturbation analysis, ordinal optimization, and beyond
Рейтинг:
Поставляется из: Англии
Описание: Discrete event systems (DES) have become pervasive in our daily lives. Examples include (but are not restricted to) manufacturing and supply chains, transportation, healthcare, call centers, and financial engineering. However, due to their complexities that often involve millions or even billions of events with many variables and constraints, modeling these stochastic simulations has long been a hard nut to crack. The advance in available computer technology, especially of cluster and cloud computing, has paved the way for the realization of a number of stochastic simulation optimization for complex discrete event systems. This book will introduce two important techniques initially proposed and developed by Professor Y C Ho and his team; namely perturbation analysis and ordinal optimization for stochastic simulation optimization, and present the state-of-the-art technology, and their future research directions.

Optimization of Stochastic Discrete Systems and Control on Complex Networks

Автор: Dmitrii Lozovanu; Stefan Pickl
Название: Optimization of Stochastic Discrete Systems and Control on Complex Networks
ISBN: 3319118323 ISBN-13(EAN): 9783319118321
Издательство: Springer
Рейтинг:
Цена: 121110.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.

Optimal Control and Optimization of Stochastic Supply Chain Systems

Автор: Dong-Ping Song
Название: Optimal Control and Optimization of Stochastic Supply Chain Systems
ISBN: 1447158547 ISBN-13(EAN): 9781447158547
Издательство: Springer
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Цена: 121890.00 T
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Описание: This book demonstrates the structural characteristics of the optimal control policies in various stochastic supply chains and to shows how to make use of these characteristics to construct easy-to-operate sub-optimal policies.

Singular Perturbation Analysis of Discrete Control Systems

Автор: Desineni S. Naidu; Ayalasomayajula K. Rao
Название: Singular Perturbation Analysis of Discrete Control Systems
ISBN: 3540159819 ISBN-13(EAN): 9783540159810
Издательство: Springer
Рейтинг:
Цена: 23250.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.

Ordinal Optimization

Автор: Yu-Chi Ho; Qian-Chuan Zhao; Qing-Shan Jia
Название: Ordinal Optimization
ISBN: 1441942432 ISBN-13(EAN): 9781441942432
Издательство: Springer
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Цена: 69650.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the difficulties of the optimization of complex systems. It does this via simulation models or other computation-intensive models involving possible stochastic effects and discrete choices.

Introduction to the Perturbation Theory of Hamiltonian Systems

Автор: Dmitry Treschev; Oleg Zubelevich
Название: Introduction to the Perturbation Theory of Hamiltonian Systems
ISBN: 3642261043 ISBN-13(EAN): 9783642261046
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book presents the basic methods of regular perturbation theory of Hamiltonian systems in an accessible fashion. It discusses all main aspects of the basic modern theory of perturbed Hamiltonian systems, and most results include complete proofs.

Stochastic Hydrology and its Use in Water Resources Systems Simulation and Optimization

Автор: J.B. Marco; R. Harboe; J.D. Salas
Название: Stochastic Hydrology and its Use in Water Resources Systems Simulation and Optimization
ISBN: 940104743X ISBN-13(EAN): 9789401047432
Издательство: Springer
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Цена: 81050.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on the NATO Advanced Study Institute, Peniscola, Spain, September 18-29, 1989

Stochastic Approximation and Optimization of Random Systems

Автор: L. Ljung; G. Pflug; H. Walk
Название: Stochastic Approximation and Optimization of Random Systems
ISBN: 3764327332 ISBN-13(EAN): 9783764327330
Издательство: Springer
Рейтинг:
Цена: 23250.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: PHug) 7 Markovian stochastic optimization and stochastic approximation procedures 53 8 Asymptotic distributions 71 9 Stopping times 79 1O Applications of stochastic approximation methods 80 References for Part II 90 III Applications to adaptation algorithms (L.

Optimization of Stochastic Discrete Systems and Control on Complex Networks

Автор: Dmitrii Lozovanu; Stefan Pickl
Название: Optimization of Stochastic Discrete Systems and Control on Complex Networks
ISBN: 3319358731 ISBN-13(EAN): 9783319358734
Издательство: Springer
Рейтинг:
Цена: 121110.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.


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