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Stochastic Optimization

Author: Stanislav Uryasev
Publisher: Springer Science & Business Media
ISBN: 1475765940
Size: 67.28 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: 14.68 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: 55.20 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: 35.93 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.

Applied Optimization

Author: Ross Baldick
Publisher: Cambridge University Press
ISBN: 1107394082
Size: 28.88 MB
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The starting point in the formulation of any numerical problem is to take an intuitive idea about the problem in question and to translate it into precise mathematical language. This book provides step-by-step descriptions of how to formulate numerical problems and develops techniques for solving them. A number of engineering case studies motivate the development of efficient algorithms that involve, in some cases, transformation of the problem from its initial formulation into a more tractable form. Five general problem classes are considered: linear systems of equations, non-linear systems of equations, unconstrained optimization, equality-constrained optimization and inequality-constrained optimization. The book contains many worked examples and homework exercises and is suitable for students of engineering or operations research taking courses in optimization. Supplementary material including solutions, lecture slides and appendices are available online at www.cambridge.org/9780521855648.

Stochastic Global Optimization

Author: Gade Pandu Rangaiah
Publisher: World Scientific
ISBN: 9814299219
Size: 67.43 MB
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Optimization has played a key role in the design, planning and operation of chemical and related processes, for several decades. Global optimization has been receiving considerable attention in the past two decades. Of the two types of techniques for global optimization, stochastic global optimization is applicable to any type of problems having non-differentiable functions, discrete variables and/or continuous variables. It, thus, shows significant promise and potential for process optimization. So far, there are no books focusing on stochastic global optimization and its applications in chemical engineering. Stochastic Global Optimization - a monograph with contributions by leading researchers in the area - bridges the gap in this subject, with the aim of highlighting and popularizing stochastic global optimization techniques for chemical engineering applications. The book, with 19 chapters in all, is broadly categorized into two sections that extensively cover the techniques and the chemical engineering applications.

Stochastic Programming

Author: Andrzej P. Ruszczyński
Publisher:
ISBN:
Size: 48.59 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.

Introduction To Applied Optimization

Author: Urmila Diwekar
Publisher: Springer Science & Business Media
ISBN: 1475737459
Size: 26.47 MB
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This text presents a multi-disciplined view of optimization, providing students and researchers with a thorough examination of algorithms, methods, and tools from diverse areas of optimization without introducing excessive theoretical detail. This second edition includes additional topics, including global optimization and a real-world case study using important concepts from each chapter. Introduction to Applied Optimization is intended for advanced undergraduate and graduate students and will benefit scientists from diverse areas, including engineers.

Optimization Methods In Finance

Author: Gérard Cornuéjols
Publisher: Cambridge University Press
ISBN: 1107056748
Size: 20.35 MB
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Full treatment, from model formulation to computational implementation, of optimization techniques that solve central problems in finance.

Stochastic Modeling And Optimization

Author: David D. Yao
Publisher: Springer Science & Business Media
ISBN: 9780387955827
Size: 76.10 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.