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Author: O. L. R. Jacobs
Publisher:
Published: 1980
Total Pages: 600
ISBN-13:
DOWNLOAD EBOOKOptimal stochastic control; Stochastic optimisation; Stochastic processes; Algorithms; Information; Parameter estimation; Applications.
Author: Masanao Aoki
Publisher: Academic Press
Published: 1967-01-01
Total Pages: 374
ISBN-13: 0080955398
DOWNLOAD EBOOKOptimization of Stochastic Systems is an outgrowth of class notes of a graduate level seminar on optimization of stochastic systems. Most of the material in the book was taught for the first time during the 1965 Spring Semester while the author was visiting the Department of Electrical Engineering, University of California, Berkeley. The revised and expanded material was presented at the Department of Engineering, University of California, Los Angeles during the 1965 Fall Semester. The systems discussed in the book are mostly assumed to be of discrete-time type with continuous state variables taking values in some subsets of Euclidean spaces. There is another class of systems in which state variables are assumed to take on at most a denumerable number of values, i.e., these systems are of discrete-time discrete-space type. Although the problems associated with the latter class of systems are many and interesting, andalthough they are amenable to deep analysis on such topics as the limiting behaviors of state variables as time indexes increase to infinity, this class of systems is not included here, partly because there are many excellent books on the subjects and partly because inclusion of these materials would easily double the size of the book.
Author: Stanislav Uryasev
Publisher: Springer Science & Business Media
Published: 2013-03-09
Total Pages: 438
ISBN-13: 1475765940
DOWNLOAD EBOOKStochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic programming approaches have been successfully used in a number of areas such as energy and production planning, telecommunications, and transportation. Recently, the practical experience gained in stochastic programming has been expanded to a much larger spectrum of applications including financial modeling, risk management, and probabilistic risk analysis. Major topics in this volume include: (1) advances in theory and implementation of stochastic programming algorithms; (2) sensitivity analysis of stochastic systems; (3) stochastic programming applications and other related topics. Audience: Researchers and academies working in optimization, computer modeling, operations research and financial engineering. The book is appropriate as supplementary reading in courses on optimization and financial engineering.
Author: O. L. R. Jacobs
Publisher:
Published: 1980
Total Pages: 574
ISBN-13:
DOWNLOAD EBOOKAuthor: Masanao Aoki
Publisher: Elsevier
Published: 2016-06-03
Total Pages: 373
ISBN-13: 1483224058
DOWNLOAD EBOOKOptimization of Stochastic Systems
Author: Chun-hung Chen
Publisher: World Scientific
Published: 2011
Total Pages: 246
ISBN-13: 9814282642
DOWNLOAD EBOOKWith 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.
Author: William M. McEneaney
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 660
ISBN-13: 1461217849
DOWNLOAD EBOOKIn view of Professor Wendell Fleming's many fundamental contributions, his profound influence on the mathematical and systems theory communi ties, his service to the profession, and his dedication to mathematics, we have invited a number of leading experts in the fields of control, optimiza tion, and stochastic systems to contribute to this volume in his honor on the occasion of his 70th birthday. These papers focus on various aspects of stochastic analysis, control theory and optimization, and applications. They include authoritative expositions and surveys as well as research papers on recent and important issues. The papers are grouped according to the following four major themes: (1) large deviations, risk sensitive and Hoc control, (2) partial differential equations and viscosity solutions, (3) stochastic control, filtering and parameter esti mation, and (4) mathematical finance and other applications. We express our deep gratitude to all of the authors for their invaluable contributions, and to the referees for their careful and timely reviews. We thank Harold Kushner for having graciously agreed to undertake the task of writing the foreword. Particular thanks go to H. Thomas Banks for his help, advice and suggestions during the entire preparation process, as well as for the generous support of the Center for Research in Scientific Computation. The assistance from the Birkhauser professional staff is also greatly appreciated.
Author: Reuven Y. Rubinstein
Publisher:
Published: 1993-10-19
Total Pages: 360
ISBN-13:
DOWNLOAD EBOOKA unified and rigorous treatment of the associated stochastic optimization problems is provided and recent advances in perturbation theory encompassed. Throughout the book emphasis is upon concepts rather than mathematical completeness with the advantage that the reader only requires a basic knowledge of probability, statistics and optimization.
Author: William T. Ziemba
Publisher: World Scientific
Published: 2006
Total Pages: 756
ISBN-13: 981256800X
DOWNLOAD EBOOKA reprint of one of the classic volumes on portfolio theory and investment, this book has been used by the leading professors at universities such as Stanford, Berkeley, and Carnegie-Mellon. It contains five parts, each with a review of the literature and about 150 pages of computational and review exercises and further in-depth, challenging problems.Frequently referenced and highly usable, the material remains as fresh and relevant for a portfolio theory course as ever.
Author: Huyên Pham
Publisher: Springer Science & Business Media
Published: 2009-05-28
Total Pages: 243
ISBN-13: 3540895000
DOWNLOAD EBOOKStochastic optimization problems arise in decision-making problems under uncertainty, and find various applications in economics and finance. On the other hand, problems in finance have recently led to new developments in the theory of stochastic control. This volume provides a systematic treatment of stochastic optimization problems applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations, and martingale duality methods. The theory is discussed in the context of recent developments in this field, with complete and detailed proofs, and is illustrated by means of concrete examples from the world of finance: portfolio allocation, option hedging, real options, optimal investment, etc. This book is directed towards graduate students and researchers in mathematical finance, and will also benefit applied mathematicians interested in financial applications and practitioners wishing to know more about the use of stochastic optimization methods in finance.
