Modern Numerical Nonlinear Optimization (Hardcover, 1st ed. 2022)

This book includes a thorough theoretical and computational analysis of unconstrained and constrained optimization algorithms and combines and integrates the most recent techniques and advanced computational linear algebra methods. Nonlinear optimization methods and techniques have reached their maturity and an abundance of optimization algorithms are available for which both the convergence properties and the numerical performances are known. This clear, friendly, and rigorous exposition discusses the theory behind the nonlinear optimization algorithms for understanding their properties and their convergence, enabling the reader to prove the convergence of his/her own algorithms. It covers cases and computational performances of the most known modern nonlinear optimization algorithms that solve collections of unconstrained and constrained optimization test problems with different structures, complexities, as well as those with large-scale real applications. The book is addressed to all those interested in developing and using new advanced techniques for solving large-scale unconstrained or constrained complex optimization problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master in mathematical programming will find plenty of recent information and practical approaches for solving real large-scale optimization problems and applications.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Springer Optimization and Its Applications, 195
Release date:	October 2022
First published:	2022
Authors:	Neculai Andrei
Dimensions:	254 x 178mm (L x W)
Format:	Hardcover
Pages:	807
Edition:	1st ed. 2022
ISBN-13:	978-3-03-108719-6
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Science & Mathematics > Mathematics > Optimization > General
LSN:	3-03-108719-4
Barcode:	9783031087196

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