Stochastic Global Optimization
This book aims to cover major methodological and theoretical developments in the field of shastic global optimization. This field includes global random search and methods based on probabilistic assumptions about the objective function. We discuss the basic ideas lying behind the main algorithmic schemes, formulate the most essential algorithms and outline the ways of their theor- ical investigation. We try to be mathematically precise and sound but at the same time we do not often delve deep into the mathematical detail, referring instead to the corresponding literature. We often do not consider the most g- eral assumptions, preferring instead simplicity of arguments. For example, we only consider continuousfinite dimensional optimization despite the fact that some of the methods can easily be modified for discrete or inflnite-dimensional optimization problems. The authors’ interests and the availability of good surveys on particular topics have in uenced the choice of material in the book. For example, there are excellent surveys on simulated annealing (both on theoretical and - plementation aspects of this method) and evolutionary algorithms (including genetic algorithms). We thus devote much less attention to these topics than they merit, concentrating instead on the issues which are not that well d- umented in literature. We also spend more time discussing the most recent ideas which have been proposed in the last few years.
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Stochastic Global Optimization
This book aims to cover major methodological and theoretical developments in the field of shastic global optimization. This field includes global random search and methods based on probabilistic assumptions about the objective function. We discuss the basic ideas lying behind the main algorithmic schemes, formulate the most essential algorithms and outline the ways of their theor- ical investigation. We try to be mathematically precise and sound but at the same time we do not often delve deep into the mathematical detail, referring instead to the corresponding literature. We often do not consider the most g- eral assumptions, preferring instead simplicity of arguments. For example, we only consider continuousfinite dimensional optimization despite the fact that some of the methods can easily be modified for discrete or inflnite-dimensional optimization problems. The authors’ interests and the availability of good surveys on particular topics have in uenced the choice of material in the book. For example, there are excellent surveys on simulated annealing (both on theoretical and - plementation aspects of this method) and evolutionary algorithms (including genetic algorithms). We thus devote much less attention to these topics than they merit, concentrating instead on the issues which are not that well d- umented in literature. We also spend more time discussing the most recent ideas which have been proposed in the last few years.
109.99
In Stock
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1
Stochastic Global Optimization
262
Stochastic Global Optimization
262
109.99
In Stock
Product Details
| ISBN-13: | 9780387740225 |
|---|---|
| Publisher: | Springer US |
| Publication date: | 11/26/2007 |
| Series: | Springer Optimization and Its Applications , #9 |
| Edition description: | 2008 |
| Pages: | 262 |
| Product dimensions: | 6.20(w) x 9.30(h) x 0.90(d) |
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