Stochastic Optimization (Scientific Computation) 2006th Edition by Johannes Schneider (PDF)

Description

This book addresses stochastic optimization procedures in a broad manner. The first part offers an overview of relevant optimization philosophies; the second deals with benchmark problems in depth, by applying a selection of optimization procedures. Written primarily with scientists and students from the physical and engineering sciences in mind, this book addresses a larger community of all who wish to learn about stochastic optimization techniques and how to use them.

User’s Reviews

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

⭐I have to say i am pretty much disappointed by this book as it did not give me what i expected from the book. The topic of optimization is a numerical topic and should be given with clear written examples from varieties of application. This book is entirely descriptive written like a fiction or a newspaper. The author claims to have been in the USA but that does warrant writing a good text. This is the book which i gain little if i read and therefore i have put it on my shelf.

⭐I suppose the goal of this book is to provide more of an overview of the heuristicsused in stochastic optimization, than to provide an analytically in-depth treatment of each subject.For this reason I felt somewhat disappointed because I expected more from a Springer book. So many of thetopics were glossed over in a manner which, although I felt that I was at least exposed to the general ideabehind a given optimization techinique, it nonethelessleft me still feeling unprepared to actually apply that technique within the context of my work.However, one bright area of the book is chapters 11-15 on simulated annealing. By reading these chaptersI came away with a better understanding of the subject, including the general method of Markov Chain Monte Carloand the Hastings Metropolis method, of which simulated annealing is derived from. It seemed obvious that theauthors knew much more about this topic than any of the others.The other issue I have with the book is the lack of variety of applications. On one hand, I can see why theauthors preferred focusing mostly on the traveling salesperson problem,so that they could hold the problem constant, while varying the techniques. But on theother, I would have preferred a variety of applications to help illuminate just why stochastic methodsseem such an essential tool for optimization in general. Even though NP-complete problems arepolynomially isomorphic it does not mean that a stochastic optimization algorithm that works well for one, willnecessarily work well for the other.I do feel thankful that I have this book on my shelf; just have a feeling that it will collect more dust than I hadhoped.

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