Evolutionary Algorithms in Engineering Applications - Info and Reading Options
By D. Dasgupta and Zbigniew Michalewicz
"Evolutionary Algorithms in Engineering Applications" was published by Springer Berlin / Heidelberg in 2010 - Berlin Heidelberg, it has 555 pages and the language of the book is English.
“Evolutionary Algorithms in Engineering Applications” Metadata:
- Title: ➤ Evolutionary Algorithms in Engineering Applications
- Authors: D. DasguptaZbigniew Michalewicz
- Language: English
- Number of Pages: 555
- Publisher: Springer Berlin / Heidelberg
- Publish Date: 2010
- Publish Location: Berlin Heidelberg
“Evolutionary Algorithms in Engineering Applications” Subjects and Themes:
- Subjects: ➤ Evolutionary programming (Computer science) - Engineering - Genetic algorithms - Data processing - Ciencias da engenharia - Programming Techniques - Algorithmes - Computer-Aided Engineering (CAD, CAE) and Design - Complexity - Computer Science - Evolutionärer Algorithmus - Programmation évolutionnaire - Computing Methodologies - Génie logiciel - Algorithmes génétiques - Engineering, data processing
Edition Specifications:
- Weight: 0.878
Edition Identifiers:
- The Open Library ID: OL34452637M - OL18361572W
- ISBN-13: 9783642082825 - 9783662034231
- All ISBNs: 9783642082825 - 9783662034231
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"Evolutionary Algorithms in Engineering Applications" Description:
Open Data:
Evolutionary algorithms are general-purpose search procedures based on the mechanisms of natural selection and population genetics. They are appealing because they are simple, easy to interface, and easy to extend. This volume is concerned with applications of evolutionary algorithms and associated strategies in engineering. It will be useful for engineers, designers, developers, and researchers in any scientific discipline interested in the applications of evolutionary algorithms. The volume consists of five parts, each with four or five chapters. The topics are chosen to emphasize application areas in different fields of engineering. Each chapter can be used for self-study or as a reference by practitioners to help them apply evolutionary algorithms to problems in their engineering domains
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