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STOCHASTIC SIMULATION OPTIMIZATION FOR DISCRETE EVENT SYSTEM

STOCHASTIC SIMULATION OPTIMIZATION FOR DISCRETE EVENT SYSTEM

STOCHASTIC SIMULATION OPTIMIZATION FOR DISCRETE EVENT SYSTEM Hardback - 2013

by CHEN CHUN-HUNG

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Details

  • Title STOCHASTIC SIMULATION OPTIMIZATION FOR DISCRETE EVENT SYSTEM
  • Author CHEN CHUN-HUNG
  • Binding Hardback
  • Condition New
  • Pages 276
  • Volumes 1
  • Language ENG
  • Publisher World Scientific Publishing Company
  • Publication date 2013-07-15
  • Features Table of Contents
  • Bookseller's Inventory # ria9789814513005_inp
  • ISBN 9789814513005 / 9814513008
  • Weight 1.15 lbs (0.52 kg)
  • Dimensions 9.1 x 6.1 x 0.8 in (23.11 x 15.49 x 2.03 cm)
  • Category Technology & Industrial Arts
  • Library of Congress subjects Perturbation (Mathematics), Discrete-time systems - Mathematical models
  • Library of Congress Catalogue Number 2013012700
  • Dewey Decimal Code 003.83
  • Quantity available 88

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Reader reviews for STOCHASTIC SIMULATION OPTIMIZATION FOR DISCRETE EVENT SYSTEM

From the publisher

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.

From the jacket flap

Discrete event systems (DES) have become pervasive in our daily life. 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 of 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.
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