Nonlinear Optimization
2011. szept. · Princeton University Press
E-könyv
464
Oldalak száma
family_home
Használható
info
reportAz értékelések és vélemények nincsenek ellenőrizve További információ
Információk az e-könyvről
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.
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.
A szerzőről
Andrzej Ruszczynski is Professor of Operations Research at Rutgers University. He is the coauthor of Stochastic Programming and the coeditor of Decision Making under Uncertainty.
E-könyv értékelése
Mondd el a véleményedet.
Olvasási információk
Okostelefonok és táblagépek
Telepítsd a Google Play Könyvek alkalmazást Android- vagy iPad/iPhone eszközre. Az alkalmazás automatikusan szinkronizálódik a fiókoddal, így bárhol olvashatsz online és offline állapotban is.
Laptopok és számítógépek
A Google Playen vásárolt hangoskönyveidet a számítógép böngészőjében is meghallgathatod.
E-olvasók és más eszközök
E-tinta alapú eszközökön (például Kobo e-könyv-olvasón) való olvasáshoz le kell tölteni egy fájlt, és átvinni azt a készülékre. A Súgó részletes utasításait követve lehet átvinni a fájlokat a támogatott e-könyv-olvasókra.
