Excerpt from A Stochastic Approach to Global Optimization, Vol. 5
Of course, this argument does not apply when one is satisfied with an approximation of the global minimum. In particular, for the case that a point within distance 6 from x* is sought, enumerative strategies exist that only require a finite number of function evaluations. These strategies, however, are of limited practical use. Thus, either a further restriction of the class of objective functions or a further relaxation of what is required Of an algorithm will be inevitable in what follows.
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Excerpt from A Stochastic Approach to Global Optimization, Vol. 5
Of course, this argument does not apply when one is satisfied with an approximation of the global minimum. In particular, for the case that a point within distance 6 from x* is sought, enumerative strategies exist that only require a finite number of function evaluations. These strategies, however, are of limited practical use. Thus, either a further restriction of the class of objective functions or a further relaxation of what is required Of an algorithm will be inevitable in what follows.
About the Publisher
Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com
This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Excerpt from A Stochastic Approach to Global Optimization, Vol. 5
A Stochastic Approach to Global Optimization was written by A. H. R. Rinnooy Kan and C. G. E. Boender in 1984. This is a 30 page book, containing 8497 words. Search Inside is enabled for this title.
About the Publisher
Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com
This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LW-9781332283033
Cantidad disponible: 15 disponibles
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Paperback. Condición: New. Print on Demand. This book posits a stochastic approach to global optimization, a mathematical theory aimed at finding the most optimal solution to complex problems with multiple variables. In contrast with traditional methods of finding local optimums, this approach permits the identification of global optimums and even offers probabilistic guarantees of success. Crucially, the author argues that this approach necessitates both a statistical and a computational fusion to overcome its inherent unsolvability. The book delves into deterministic methods, their drawbacks, and additional algorithms designed to overcome the limitations of existing approaches. It also explores the practical implementation of stochastic methods through clustering techniques that improve efficiency. Overall, the book's innovative insights make it essential reading for researchers, practitioners, and students interested in optimization and its applications in various fields. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Nº de ref. del artículo: 9781332283033_0
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