Non-Linear Parametric Optimization PDF Download

Author: BANK
Publisher: Birkhäuser
ISBN: 3034863284
Category : Science
Languages : en
Pages : 227

View

Book Description

Author: B. Bank
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3112706919
Category : Mathematics
Languages : en
Pages : 228

View

Book Description
No detailed description available for "Non-Linear Parametric Optimization".

Author: Stig I Andersson
Publisher:
ISBN: 9782387127105
Category :
Languages : en
Pages : 334

View

Book Description

Author: Fred Glover
Publisher:
ISBN:
Category :
Languages : en
Pages : 49

View

Book Description

Author: John C. Nash
Publisher: John Wiley & Sons
ISBN: 1118883969
Category : Mathematics
Languages : en
Pages : 304

View

Book Description
Nonlinear Parameter Optimization Using R John C. Nash, Telfer School of Management, University of Ottawa, Canada A systematic and comprehensive treatment of optimization software using R In recent decades, optimization techniques have been streamlined by computational and artificial intelligence methods to analyze more variables, especially under non–linear, multivariable conditions, more quickly than ever before. Optimization is an important tool for decision science and for the analysis of physical systems used in engineering. Nonlinear Parameter Optimization with R explores the principal tools available in R for function minimization, optimization, and nonlinear parameter determination and features numerous examples throughout. Nonlinear Parameter Optimization with R: Provides a comprehensive treatment of optimization techniques Examines optimization problems that arise in statistics and how to solve them using R Enables researchers and practitioners to solve parameter determination problems Presents traditional methods as well as recent developments in R Is supported by an accompanying website featuring R code, examples and datasets Researchers and practitioners who have to solve parameter determination problems who are users of R but are novices in the field optimization or function minimization will benefit from this book. It will also be useful for scientists building and estimating nonlinear models in various fields such as hydrology, sports forecasting, ecology, chemical engineering, pharmaco-kinetics, agriculture, economics and statistics.

Author: Jürgen Guddat
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 208

View

Book Description
Explores optimization problems in which some or all of the individual data involved depends on one parameter. Beginning with a preliminary survey of solution algorithms in one-parametric optimization, the text moves on to examine the pathfollowing curves of local minimizers, pathfollowing along a connected component in the Karush-Kuhn-Tucker set and in the critical set, pathfollowing in the set of local minimizers and in the set of critical points. In addition, practical applications are included.

Author: Rüdiger Schmidt
Publisher: Springer
ISBN:
Category : Mathematics
Languages : en
Pages : 174

View

Book Description

Author: R. Schmidt
Publisher: Springer
ISBN: 9783662196465
Category : Science
Languages : en
Pages : 163

View

Book Description

Author: Gianni Pillo
Publisher: Springer Science & Business Media
ISBN: 0387300651
Category : Mathematics
Languages : en
Pages : 297

View

Book Description
This book reviews and discusses recent advances in the development of methods and algorithms for nonlinear optimization and its applications, focusing on the large-dimensional case, the current forefront of much research. Individual chapters, contributed by eminent authorities, provide an up-to-date overview of the field from different and complementary standpoints, including theoretical analysis, algorithmic development, implementation issues and applications.

Author: Andrzej Ruszczynski
Publisher: Princeton University Press
ISBN: 1400841054
Category : Mathematics
Languages : en
Pages : 463

View

Book Description
Optimization is one of the most important areas of modern applied mathematics, with applications in fields from engineering and economics to finance, statistics, management science, and medicine. While many books have addressed its various aspects, Nonlinear Optimization is the first comprehensive treatment that will allow graduate students and researchers to understand its modern ideas, principles, and methods within a reasonable time, but without sacrificing mathematical precision. Andrzej Ruszczynski, a leading expert in the optimization of nonlinear stochastic systems, integrates the theory and the methods of nonlinear optimization in a unified, clear, and mathematically rigorous fashion, with detailed and easy-to-follow proofs illustrated by numerous examples and figures. The book covers convex analysis, the theory of optimality conditions, duality theory, and numerical methods for solving unconstrained and constrained optimization problems. It addresses not only classical material but also modern topics such as optimality conditions and numerical methods for problems involving nondifferentiable functions, semidefinite programming, metric regularity and stability theory of set-constrained systems, and sensitivity analysis of optimization problems. Based on a decade's worth of notes the author compiled in successfully teaching the subject, this book will help readers to understand the mathematical foundations of the modern theory and methods of nonlinear optimization and to analyze new problems, develop optimality theory for them, and choose or construct numerical solution methods. It is a must for anyone seriously interested in optimization.