Numerical Methods and Optimization, Butenko, Sergiy
Автор: David Yang Gao; Raymond W. Ogden; Georgios E. Stav Название: Nonsmooth/Nonconvex Mechanics ISBN: 1461379733 ISBN-13(EAN): 9781461379737 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Manfred Gilli Название: Numerical Methods and Optimization in Finance, ISBN: 0123756626 ISBN-13(EAN): 9780123756626 Издательство: Elsevier Science Рейтинг: Цена: 13978.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This bookdescribes computational financetools. It covers fundamental numerical analysis and computational techniques, such asoption pricing, and givesspecial attention tosimulation and optimization. Many chapters are organized as case studies aroundportfolio insurance and risk estimation problems. In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.
Автор: Emmanuel Laporte; Patrick Le Tallec Название: Numerical Methods in Sensitivity Analysis and Shape Optimization ISBN: 1461265983 ISBN-13(EAN): 9781461265986 Издательство: Springer Рейтинг: Цена: 9141.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Numerical Methods in Sensitivity Analysis and Shape Optimization will be of interest to graduate students involved in mathematical modeling and simulation, as well as engineers and researchers in applied mathematics looking for an up-to-date introduction to optimization techniques, sensitivity analysis, and optimal design.
Описание: This book collects results in numerical analysis and optimization presented at the 2011 ECCOMAS thematic conference "Computational Analysis and Optimization." The conference and the book celebrate the work of Prof. Pekka Neittaanmaki on his sixtieth birthday.
Автор: ?ric Walter Название: Numerical Methods and Optimization ISBN: 3319377116 ISBN-13(EAN): 9783319377117 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
From Calculus to Computation.- Notation and Norms.- Solving Systems of Linear Equations.- Solving Other Problems in Linear Algebra.- Interpolation and Extrapolation.- Integrating and Differentiating Functions.- Solving Systems of Nonlinear Equations.- Introduction to Optimization.- Optimizing Without Constraint.- Optimizing Under Constraints.- Combinatorial Optimization.- Solving Ordinary Differential Equations.- Solving Partial Differential Equations.- Assessing Numerical Errors.- WEB Resources to go Further.- Problems.
Название: Numerical Methods and Optimization ISBN: 3030893650 ISBN-13(EAN): 9783030893651 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Нет в наличии.
Описание: This text, covering a very large span of numerical methods and optimization, is primarily aimed at advanced undergraduate and graduate students. The reader is progressively introduced to general numerical methods and optimization algorithms in each chapter.
Автор: ?ric Walter Название: Numerical Methods and Optimization ISBN: 3319076701 ISBN-13(EAN): 9783319076706 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Address vector and matrix methods necessary in numerical methods and optimization of linear systems with this practical, unified text. Perfect for advanced undergraduate students and graduate students in engineering, physical sciences, and applied mathematics.
Автор: Gilli, Manfred Название: Numerical Methods and Optimization in Finance ISBN: 0128150653 ISBN-13(EAN): 9780128150658 Издательство: Elsevier Science Рейтинг: Цена: 19875.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems-ranging from asset allocation to risk management and from option pricing to model calibration-can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically.
This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance.
Introduces numerical methods to readers with economics backgrounds
Emphasizes core simulation and optimization problems
Includes MATLAB and R code for all applications, with sample code in the text and freely available for download
Mark H.A. Davis introduced the Piecewise-Deterministic Markov Process (PDMP) class of stochastic hybrid models in an article in 1984. Today it is used to model a variety of complex systems in the fields of engineering, economics, management sciences, biology, Internet traffic, networks and many more. Yet, despite this, there is very little in the way of literature devoted to the development of numerical methods for PDMDs to solve problems of practical importance, or the computational control of PDMPs.
This book therefore presents a collection of mathematical tools that have been recently developed to tackle such problems. It begins by doing so through examples in several application domains such as reliability. The second part is devoted to the study and simulation of expectations of functionals of PDMPs. Finally, the third part introduces the development of numerical techniques for optimal control problems such as stopping and impulse control problems.
Автор: Bendsoe M.P., Sigmund O. Название: Topology Optimization: Theory, Methods and Applications ISBN: 3540429921 ISBN-13(EAN): 9783540429920 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The topology optimization method solves the basic engineering problem of distributing a limited amount of material in a design space. The first edition of this book has become the standard text on optimal design, which is concerned with the optimization of structural topology, shape and material. This edition has been substantially revised and updated to reflect progress made in modelling and computational procedures. It also encompasses a comprehensive and unified description of the state of the art of the so-called material distribution method, based on the use of mathematical programming and finite elements. Applications treated include not only structures but also MEMS and materials.
Автор: Ming-Jun Lai, Yang Wang Название: Sparse Solutions of Underdetermined Linear Systems ISBN: 1611976502 ISBN-13(EAN): 9781611976502 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11161.00 р. Наличие на складе: Нет в наличии.
Описание: This textbook presents a special solution of underdetermined linear systems where the number of nonzero entries in the solution is very small compared to the total number of entries. This is called sparse solution. As underdetermined linear systems can be very different, the authors explain how to compute a sparse solution by many approaches.Sparse Solutions of Underdetermined Linear Systems:Contains 72 algorithms for finding sparse solutions of underdetermined linear systems and their applications for matrix completion, graph clustering, and phase retrieval.Provides a detailed explanation of these algorithms including derivations and convergence analysis.Includes exercises for each chapter to help the reader understand the material.This textbook is appropriate for graduate students in math and applied math, computer science, statistics, data science, and engineering. Advisors and postdocs will also find the book of interest.It is appropriate for the following courses: Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory.
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