Numerical Optimization (Springer Series in Operations Research and Financial Engineering) 2nd Edition by Jorge Nocedal | (PDF) Free Download

Description

Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐This is a must-read book for anyone who wishes to study Numerical Analysis on a professional level. This text will teach many fundamental principals of applied analysis by walking the reader through an extremely wide array of finite dimensional optimization algorithms.

⭐Trained a physicist before I went into applied math and computer science I thoroughly enjoy this book. It math is not light but not that heavy either. I wouldn’t consider it math at graduate level as most of the material is applicable to an undergrad with 1 year of calculus and another of linear algebra. A bit more of statistical elaborations might be useful for a third edition, given the current focus on machine learning. Anyhow as a first book it is still excellent.

⭐Not the easiest to read at times but a classic, solid math and algorithms book. Comprehensive appendix for the math used, detailed (enough) proofs for the material presented and a good balance between examples and theory.

⭐The best text book on the various issues around steepest descent, conjugate gradient, Newtonian methods etc. Clearly show you why you still need to care about steepest-descent even though we were taught it is much slower than Newton or CG. Those that are practical oriented might have ignored the key role SD play in many methods to guarantee convergence (or progress).Very good write up on the Wolfe condition, Cauchy point, and trust region.

⭐This book is essential for any optimization guy. Provides most of the available methods including: stochastic gradient, steepest descent, newtons, trust-region methodologies.One of the authors was my professor. So, I am biased toward the quality and the material in this book. Because, indeed the author would deliver the material in a much nicer way than others.

⭐This book is the best reference on the different optimization algorithms in use today. It is a very practical book and I find myself referring to it often.

⭐The book is quite complete and goes directly to the point. if you ever need optimization in your design you will find it here. Simple and well presented. It has enough details about algorithmic performance and description that should be enough to implement. It is a book that you will never regret having it in your library. If you want something more theoretical use

⭐by Bertsekas. If you want to use optimization in your programs use this.

⭐This book is a well-written, outstanding reference for anyone interested in understanding, using, and/or implementing state-of-the-art techniques in nonlinear optimization. Ample attention is paid to both constrained and unconstrained problem types, with a healthy and refreshing emphasis on trust-region strategies, and modern SQP and Interior-Point algorithms. Sufficient detail is paid to most topics while overall perspectives are well-maintained. This book is the very best of its kind for its intended audience. I strongly recommend it.

⭐Nice book, but the hardcover could be a little bit too heavy. Overall speaking, it’s a very nice book.

⭐An der sicherlich nicht negativ gemeinten Kundenbewertung von Minh Duc Hoang erkennt man mal wieder denkompletten Unfug, den die blödsinnige Sternebewertung darstellt (leider kann man sie ja beimSchreiben einer Rezension nicht umgehen). Hier wird nichtder Inhalt, sondern die Lieferung bewertet. Das ist sicherlich das gute Recht eines Rezensentenund deshalb überhaupt kein Vorwurf an Minh Duc Hoang! Der Fehler liegt bei Amazon!!Nach außen sind erstmal nur die drei Sterne zu sehen und kein Mensch weißzunächst, dass gar nicht der Inhalt rezensiert wurde.Ich hoffe, dass irgendwann einmal jemand diesen Sterne-Mist abstellt!Drei Sterne für so ein hervorragendes Buch?Es hätte 30 Sterne verdient! Ich habe selten so ein verständlich geschriebenes und zugleich dochtiefgehendes Buch gelesen. Hier geht es wirklich darum, dem Leser zunächst die Ideen zu vermitteln,bevor die Details der Beweise diskutiert werden. So sollte ein Mathematik-Buch sein!Wonderful book .. I used it while completing a course. The book covers a wide domain of subjects and it is useful as a self study as well .. if you have the right background and interest of course.

⭐Aparte de que es un excelente libro (por eso lo ordené), llegó en tiempo estimado, y en muy buenas condiciones.Buen libro para ser autodidadcta

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