9783030854492 - linear and nonlinear programming: 228 di luenberger, david g.; ye, yinyu (30 risultati)
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Editore: Springer 2021
Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Hardback. Condizione: New. Fifth Edition 2021. The 5th edition of this classic textbook covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytical character of an optimization problem a…nd the behavior of algorithms used to solve that problem. End-of-chapter exercises are provided for all chapters. The material is organized into three separate parts. Part I offers a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. In turn, Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. As such, Parts II and III can easily be used without reading Part I and, in fact, the book has been used in this way at many universities. New to this edition are popular topics in data science and machine learning, such as the Markov Decision Process, Farkas' lemma, convergence speed analysis, duality theories and applications, various first-order methods, stochastic gradient method, mirror-descent method, Frank-Wolf method, ALM/ADMM method, interior trust-region method for non-convex optimization, distributionally robust optimization, online linear programming, semidefinite programming for sensor-network localization, and infeasibility detection for nonlinear optimization.
Lingua: Inglese
Editore: Springer 2021
Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
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Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Hardback. Condizione: New. Fifth Edition 2021. The 5th edition of this classic textbook covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytical character of an optimization problem a…nd the behavior of algorithms used to solve that problem. End-of-chapter exercises are provided for all chapters. The material is organized into three separate parts. Part I offers a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. In turn, Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. As such, Parts II and III can easily be used without reading Part I and, in fact, the book has been used in this way at many universities. New to this edition are popular topics in data science and machine learning, such as the Markov Decision Process, Farkas' lemma, convergence speed analysis, duality theories and applications, various first-order methods, stochastic gradient method, mirror-descent method, Frank-Wolf method, ALM/ADMM method, interior trust-region method for non-convex optimization, distributionally robust optimization, online linear programming, semidefinite programming for sensor-network localization, and infeasibility detection for nonlinear optimization.
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Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The 5th edition of this classic textbook covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytical character… of an optimization problem and the behavior of algorithms used to solve that problem. End-of-chapter exercises are provided for all chapters.The material is organized into three separate parts. Part I offers a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. In turn, Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. As such, Parts II and III can easily be used without reading Part I and, in fact, the book has been used in this way at many universities.New to this edition are popular topics in data science and machine learning, such as the Markov Decision Process, Farkas' lemma, convergence speed analysis, duality theories and applications, various first-order methods, stochastic gradient method, mirror-descent method, Frank-Wolf method, ALM/ADMM method, interior trust-region method for non-convex optimization, distributionally robust optimization, online linear programming, semidefinite programming for sensor-network localization, and infeasibility detection for nonlinear optimization.
Lingua: Inglese
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Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Hardcover. Condizione: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be re…quested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Lingua: Inglese
Editore: Springer 2021
Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Hardcover. Condizione: Brand New. 5th edition. 624 pages. 9.25x6.10x1.46 inches. In Stock.
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Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The 5th edition of this classic textbook covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely anal…ytical character of an optimization problem and the behavior of algorithms used to solve that problem. End-of-chapter exercises are provided for all chapters.The material is organized into three separate parts. Part I offers a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. In turn, Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. As such, Parts II and III can easily be used without reading Part I and, in fact, the book has been used in this way at many universities.New to this edition are popular topics in data science and machine learning, such as the Markov Decision Process, Farkas' lemma, convergence speed analysis, duality theories and applications, various first-order methods, stochastic gradient method, mirror-descent method, Frank-Wolf method, ALM/ADMM method, interior trust-region method for non-convex optimization, distributionally robust optimization, online linear programming, semidefinite programming for sensor-network localization, and infeasibility detection for nonlinear optimization. 628 pp. Englisch.
Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|Springer 2022
Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The 5th edition of this classic textbook covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection b…etween the purely analytical character.
Lingua: Inglese
Editore: Springer, Springer Nov 2021 2021
Serie: International Series in Operations Research & Management Science, Libro 304 di 323. Libro 304 di 323 - International Series in Operations Research & Management Science
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Da: buchversandmimpf2000, Emtmannsberg, Germaniabuchversandmimpf2000
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The 5th edition of this classic textbook covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytic…al character of an optimization problem and the behavior of algorithms used to solve that problem. End-of-chapter exercises are provided for all chapters.The material is organized into three separate parts. Part I offers a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. In turn, Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. As such, Parts II and III can easily be used without reading Part I and, in fact, the book has been used in this way at many universities.New to this edition are popular topics in data science and machine learning, such as the Markov Decision Process, Farkas¿ lemma, convergence speed analysis, duality theories and applications, various first-order methods, stochastic gradient method, mirror-descent method, Frank-Wolf method, ALM/ADMM method, interior trust-region method for non-convex optimization, distributionally robust optimization, online linear programming, semidefinite programming for sensor-network localization, and infeasibility detection for nonlinear optimization.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 628 pp. Englisch.
