Engineering design optimization /
Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimi...
| Main Authors: | , |
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| Format: | Book |
| Language: | English |
| Published: |
Cambridge ; New York :
Cambridge University Press,
[2022].
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| Subjects: |
| Summary: | Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 200 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. |
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| Physical Description: | xiii, 637 pages : illustrations (some color) ; 26 cm. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781108833417 1108833411 |