Hardcover. Condition: new. Hardcover. 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 400 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. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments. A rigorous yet accessible textbook covering both fundamental and advanced optimization topics. Covering both gradient-based and gradient-free algorithms, derivative computation, and numerous visualizations, examples and problems, it is ideal for graduate courses on optimization in aerospace, civil, and mechanical engineering departments. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781108833417

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Engineering Design Optimization

Andrew Ning

Published by Cambridge University Press, 2021

ISBN 10: 1108833411 ISBN 13: 9781108833417

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Engineering Design Optimization (Hardcover)

Andrew Ning

Published by Cambridge University Press, Cambridge, 2021

ISBN 10: 1108833411 ISBN 13: 9781108833417

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Hardcover. Condition: new. Hardcover. 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 400 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. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments. A rigorous yet accessible textbook covering both fundamental and advanced optimization topics. Covering both gradient-based and gradient-free algorithms, derivative computation, and numerous visualizations, examples and problems, it is ideal for graduate courses on optimization in aerospace, civil, and mechanical engineering departments. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781108833417

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