A rigorous yet accessible graduate textbook covering both fundamental and advanced optimization theory and algorithms.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Joaquim R. R. A. Martins is a Professor of Aerospace Engineering at the University of Michigan. He is a fellow of the American Institute for Aeronautics and Astronautics, and the Royal Aeronautical Society.
Andrew Ning is an Associate Professor of Mechanical Engineering at Brigham Young University, and has previously worked at the National Renewable Energy Laboratory (NREL) as a Senior Engineer.
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Destinazione, tempi e costiDa: PBShop.store US, Wood Dale, IL, U.S.A.
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo FM-9781108833417
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Da: PBShop.store UK, Fairford, GLOS, Regno Unito
HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo FM-9781108833417
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 43002936-n
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Da: California Books, Miami, FL, U.S.A.
Condizione: New. Codice articolo I-9781108833417
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Da: Revaluation Books, Exeter, Regno Unito
Hardcover. Condizione: Brand New. 637 pages. 10.25x7.75x1.25 inches. In Stock. Codice articolo __1108833411
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Da: moluna, Greven, Germania
Condizione: New. 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 co. Codice articolo 485626209
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 43002936
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Da: CitiRetail, Stevenage, Regno Unito
Hardcover. Condizione: 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. Codice articolo 9781108833417
Quantità: 1 disponibili
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Condizione: New. Codice articolo ABLIING23Mar2317530288331
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Da: Revaluation Books, Exeter, Regno Unito
Hardcover. Condizione: Brand New. 637 pages. 10.25x7.75x1.25 inches. In Stock. Codice articolo x-1108833411
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