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Stochastic Optimization

Author: Stanislav Uryasev
Publisher: Springer Science & Business Media
ISBN: 1475765940
Size: 39.15 MB
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Stochastic 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.

Advances In Structural And Multidisciplinary Optimization

Author: Axel Schumacher
Publisher: Springer
ISBN: 3319679880
Size: 10.96 MB
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The volume includes papers from the WSCMO conference in Braunschweig 2017 presenting research of all aspects of the optimal design of structures as well as multidisciplinary design optimization where the involved disciplines deal with the analysis of solids, fluids or other field problems. Also presented are practical applications of optimization methods and the corresponding software development in all branches of technology.

Optimization In The Energy Industry

Author: Josef Kallrath
Publisher: Springer Science & Business Media
ISBN: 3540889655
Size: 74.54 MB
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This book offers a broad, in-depth overview that reflects the requirements, possibilities and limits of mathematical optimization and, especially, stochastic optimization in the energy industry.

Pattern Recognition

Author: Volker Roth
Publisher: Springer
ISBN: 3319667092
Size: 74.11 MB
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This book constitutes the refereed proceedings of the 39th German Conference on Pattern Recognition, GCPR 2017, held in Basel, Switzerland, in September 2017.The 33 revised full papers presented were carefully reviewed and selected from 60 submissions. The papers are organized in topical sections on biomedical image processing and analysis; classification and detection; computational photography; image and video processing; machine learning and pattern recognition; mathematical foundations, statistical data analysis and models; motion and segmentation; pose, face and gesture; reconstruction and depth; and tracking.

Stochastic Programming

Author: Andrzej P. Ruszczyński
Size: 34.52 MB
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The area of stochastic programming was created in the middle of the last century, following fundamental achievements in linear and nonlinear programming. However, because of the inherent difficulty of stochastic optimization problems, it took a long time until efficient solution methods were developed. In the last two decades a dramatic change in our abilities to solve stochastic programming problems took place. This Handbook Volume brings together leading experts in the most important sub-fields of stochastic programming to present a rigorous overview of basic models, methods and applications of stochastic programming. The work is intended for researchers, students, engineers and economists, who encounter in their work optimization problems involving uncertainty. Important research volume for Management Scientists, Operations Researchers, Industrial Engineers, Econometricians, and Applied Mathematicians.

Stochastic Modeling And Optimization

Author: David D. Yao
Publisher: Springer Science & Business Media
ISBN: 9780387955827
Size: 20.53 MB
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This books covers the broad range of research in stochastic models and optimization. Applications presented include networks, financial engineering, production planning, and supply chain management. Each contribution is aimed at graduate students working in operations research, probability, and statistics.

Introduction To Stochastic Programming

Author: John Birge
Publisher: Springer Science & Business Media
ISBN: 9780387982175
Size: 29.49 MB
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This rapidly developing field encompasses many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors present a broad overview of the main themes and methods of the subject, thus helping students develop an intuition for how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. The early chapters introduce some worked examples of stochastic programming, demonstrate how a stochastic model is formally built, develop the properties of stochastic programs and the basic solution techniques used to solve them. The book then goes on to cover approximation and sampling techniques and is rounded off by an in-depth case study. A well-paced and wide-ranging introduction to this subject.

Modeling And Optimization Theory And Applications

Author: Martin Takáč
Publisher: Springer
ISBN: 3319666169
Size: 23.50 MB
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This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on August 17-19, 2016. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of deterministic and stochastic optimization techniques in energy, finance, logistics, analytics, health, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.