Advances In Stochastic Simulation Methods


Advances In Stochastic Simulation Methods
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Advances In Stochastic Simulation Methods


Advances In Stochastic Simulation Methods
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Author : N. Balakrishnan
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Advances In Stochastic Simulation Methods written by N. Balakrishnan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


This is a volume consisting of selected papers that were presented at the 3rd St. Petersburg Workshop on Simulation held at St. Petersburg, Russia, during June 28-July 3, 1998. The Workshop is a regular international event devoted to mathematical problems of simulation and applied statistics organized by the Department of Stochastic Simulation at St. Petersburg State University in cooperation with INFORMS College on Simulation (USA). Its main purpose is to exchange ideas between researchers from Russia and from the West as well as from other coun tries throughout the World. The 1st Workshop was held during May 24-28, 1994, and the 2nd workshop was held during June 18-21, 1996. The selected proceedings of the 2nd Workshop was published as a special issue of the Journal of Statistical Planning and Inference. Russian mathematical tradition has been formed by such genius as Tchebysh eff, Markov and Kolmogorov whose ideas have formed the basis for contempo rary probabilistic models. However, for many decades now, Russian scholars have been isolated from their colleagues in the West and as a result their mathe matical contributions have not been widely known. One of the primary reasons for these workshops is to bring the contributions of Russian scholars into lime light and we sincerely hope that this volume helps in this specific purpose.



Advances In Stochastic Simulation Methods


Advances In Stochastic Simulation Methods
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Author : N. Balakrishnan
language : en
Publisher: Boston : Birkhäuser
Release Date : 2000-01-01

Advances In Stochastic Simulation Methods written by N. Balakrishnan and has been published by Boston : Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01-01 with Computer simulation categories.


This carefully edited book discusses new methods and applications for stochastic simulation and experimental design with the focus on methodological issues and recent developments for computer simulations in statistical application problems. A large number of topics are treated, including computer simulation methodology queueing systems, statistical methods in simulation, optimal experimental design, and numerical algorithms. The book will be an essential up-to-date resource for researchers and professionals in applied statistics, experimental design, operations research and stochastic simulation.



Stochastic Simulation And Monte Carlo Methods


Stochastic Simulation And Monte Carlo Methods
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Author : Carl Graham
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-07-16

Stochastic Simulation And Monte Carlo Methods written by Carl Graham and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-16 with Mathematics categories.


In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners’ aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view. The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations.



Recent Advances In Stochastic Modeling And Data Analysis


Recent Advances In Stochastic Modeling And Data Analysis
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Author : Christos H Skiadas
language : en
Publisher: World Scientific
Release Date : 2007-11-16

Recent Advances In Stochastic Modeling And Data Analysis written by Christos H Skiadas and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-16 with Mathematics categories.


This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover various fields such as stochastic processes and applications, data analysis methods and techniques, Bayesian methods, biostatistics, econometrics, sampling, linear and nonlinear models, networks and queues, survival analysis, and time series. The volume presents new results with potential for solving real-life problems and provides novel methods for solving these problems by analyzing the relevant data. The use of recent advances in different fields is emphasized, especially new optimization and statistical methods, data warehouse, data mining and knowledge systems, neural computing, and bioinformatics.



Stochastic Simulation Optimization


Stochastic Simulation Optimization
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Author : Chun-hung Chen
language : en
Publisher: World Scientific
Release Date : 2011

Stochastic Simulation Optimization written by Chun-hung Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.


With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be very expensive. Stochastic Simulation Optimization addresses the pertinent efficiency issue via smart allocation of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation and a discussion of its impact on optimization performance, a series of OCBA approaches developed for various problems are then presented, from the selection of the best design to optimization with multiple objectives. Finally, this book discusses the potential extension of OCBA notion to different applications such as data envelopment analysis, experiments of design and rare-event simulation.



Stochastic Modeling Of Manufacturing Systems


Stochastic Modeling Of Manufacturing Systems
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Author : George Liberopoulos
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-12

Stochastic Modeling Of Manufacturing Systems written by George Liberopoulos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-12 with Business & Economics categories.


Manufacturing systems rarely perform exactly as expected and predicted. Unexpected events, such as order changes, equipment failures and product defects, affect the performance of the system and complicate decision-making. This volume is devoted to the development of analytical methods aiming at responding to variability in a way that limits its corrupting effects on system performance. The book includes fifteen novel chapters that mostly focus on the development and analysis of performance evaluation models of manufacturing systems using decomposition-based methods, Markovian and queuing analysis, simulation, and inventory control approaches. They are organized into four distinct sections to reflect their shared viewpoints: factory design, unreliable production lines, queuing network models, production planning and assembly.



Handbook Of Simulation Optimization


Handbook Of Simulation Optimization
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Author : Michael C Fu
language : en
Publisher: Springer
Release Date : 2014-11-13

Handbook Of Simulation Optimization written by Michael C Fu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-13 with Business & Economics categories.


The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.



Recent Developments In Stochastic Methods And Applications


Recent Developments In Stochastic Methods And Applications
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Author : Albert N. Shiryaev
language : en
Publisher: Springer Nature
Release Date : 2021-08-02

Recent Developments In Stochastic Methods And Applications written by Albert N. Shiryaev and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-02 with Mathematics categories.


Highlighting the latest advances in stochastic analysis and its applications, this volume collects carefully selected and peer-reviewed papers from the 5th International Conference on Stochastic Methods (ICSM-5), held in Moscow, Russia, November 23-27, 2020. The contributions deal with diverse topics such as stochastic analysis, stochastic methods in computer science, analytical modeling, asymptotic methods and limit theorems, Markov processes, martingales, insurance and financial mathematics, queueing theory and stochastic networks, reliability theory, risk analysis, statistical methods and applications, machine learning and data analysis. The 29 articles in this volume are a representative sample of the 87 high-quality papers accepted and presented during the conference. The aim of the ICSM-5 conference is to promote the collaboration of researchers from Russia and all over the world, and to contribute to the development of the field of stochastic analysis and applications of stochastic models.



Advanced Simulation Based Methods For Optimal Stopping And Control


Advanced Simulation Based Methods For Optimal Stopping And Control
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Author : Denis Belomestny
language : en
Publisher: Springer
Release Date : 2018-01-31

Advanced Simulation Based Methods For Optimal Stopping And Control written by Denis Belomestny and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-31 with Business & Economics categories.


This is an advanced guide to optimal stopping and control, focusing on advanced Monte Carlo simulation and its application to finance. Written for quantitative finance practitioners and researchers in academia, the book looks at the classical simulation based algorithms before introducing some of the new, cutting edge approaches under development.



Recent Advances In Stochastic Operations Research Ii


Recent Advances In Stochastic Operations Research Ii
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Author : Tadashi Dohi
language : en
Publisher: World Scientific
Release Date : 2009

Recent Advances In Stochastic Operations Research Ii written by Tadashi Dohi and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Business & Economics categories.


Operations research uses quantitative models to analyze and predict the behavior of systems and to provide information for decision makers. Two key concepts in such research are optimization and uncertainty. Typical models in stochastic operations research include queueing models, inventory models, financial engineering models, reliability models, and simulation models. This book contains a collection of peer-reviewed papers from the International Workshop on Recent Advances in Stochastic Operations Research (2007 RASOR Nanzan) held on March 5OCo6, 2007, at Nanzan University, Nagoya, Japan. It enables advanced readers to understand the recent topics and results in stochastic operations research.