Author: Andrzej Osyczka
Edition: 1
Publisher: Physica-Verlag HD
Binding: Hardcover
ISBN: 3790814180
Category: Programming
List Price: $ 89.95
Price: $ 89.95
You Save: 0%
Evolutionary Algorithms for Single and Multicriteria Design Optimization (Studies in Fuzziness and Soft Computing)
Many design optimization problems are of a very complex nature and quite hard to solve by conventional optimization techniques. Programming books Evolutionary Algorithms for Single and Multicriteria Design Optimization pdf. Genetic and evolutionary algorithms have recently received considerable attention because of their potential of being a very effective design optimization technique. The book starts with an introduction to design optimization which is followed by a description of genetic and evolutionary algorithms. Then the advanced evolutionary algorithm techniques are provided. These techniques are used in the single and multicriteria optimization methods described in this book. Download books Computational Intelligence in Expensive Optimization Problems (Hardcover) pdf via mediafire, 4shared, rapidshare.
Price comparison for Computational Intelligence in Expensive Optimization Problems
Price: $329
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc.
Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc.
Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary
Price: $319.85
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc.Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary a
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc.Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary a
Price: $329
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc.
Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc.
Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary
Price: $259
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc.
Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc.
Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary
Price: $3.9
Review "Bioinspired computing is successful in practice. Over the past decade a body of theory for bioinspired computing has been developed. The authors have contributed significantly to this body and give a highly readable account of it." Kurt Mehlhorn, Max Planck Institute for Informatics, and Saarland University, Germany"Bioinspired algorithms belong to the most powerful methods used to tackle real world optimization problems. This book gives such algorithms a solid foundation. It presents some of the most exciting results that have been obtained in bioinspired computing in the last decade.
Review "Bioinspired computing is successful in practice. Over the past decade a body of theory for bioinspired computing has been developed. The authors have contributed significantly to this body and give a highly readable account of it." Kurt Mehlhorn, Max Planck Institute for Informatics, and Saarland University, Germany"Bioinspired algorithms belong to the most powerful methods used to tackle real world optimization problems. This book gives such algorithms a solid foundation. It presents some of the most exciting results that have been obtained in bioinspired computing in the last decade.
Download Evolutionary Algorithms for Single and Multicriteria Design Optimization
Genetic and evolutionary algorithms have recently received considerable attention because of their potential of being a very effective design optimization technique. The book starts with an introduction to design optimization which is followed by a description of genetic and evolutionary algorithms. Then the advanced evolutionary algorithm techniques are provided. These techniques are used in the single and multicriteria optimization methods described in this book. Finally three real-life design optimization problems are formulated and solved by means of these methods. The book is designed as a self-study guide for researchers and students in all engineering departments, especially in mechanical, civil and industrial engineering. The book may also be useful as a comprehensive text for operations researchers, artifical intelligence researchers. Download free Evolutionary Algorithms for Single and Multicriteria Design Optimization (Studies in Fuzziness and Soft Computing) pdf
No comments:
Post a Comment