A concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory.
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Destinos, gastos y plazos de envíoLibrería: Better World Books, Mishawaka, IN, Estados Unidos de America
Condición: Good. Used book that is in clean, average condition without any missing pages. Nº de ref. del artículo: 15882747-6
Cantidad disponible: 1 disponibles
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 1514175
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Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Paperback. Condición: New. This reprint of the 1969 book of the same name is a concise, rigorous, yet accessible account of the fundamentals of constrained optimization theory. Many problems arising in diverse fields such as machine learning, medicine, chemical engineering, structural design, and airline scheduling can be reduced to a constrained optimization problem. This book provides readers with the fundamentals needed to study and solve such problems.Beginning with a chapter on linear inequalities and theorems of the alternative, basics of convex sets and separation theorems are then derived based on these theorems. This is followed by a chapter on convex functions that includes theorems of the alternative for such functions. These results are used in obtaining the saddlepoint optimality conditions of nonlinear programming without differentiability assumptions. Properties of differentiable convex functions are derived and then used in two key chapters of the book, one on optimality conditions for differentiable nonlinear programs and one on duality in nonlinear programming. Generalizations of convex functions to pseudoconvex and quasiconvex functions are given and then used to obtain generalized optimality conditions and duality results in the presence of nonlinear equality constraints.The book has four useful self-contained appendices on vectors and matrices, topological properties of n-dimensional real space, continuity and minimization, and differentiable functions. Nº de ref. del artículo: LU-9780898713411
Cantidad disponible: 1 disponibles
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 1514175-n
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Condición: New. 1987. Paperback. . . . . . Nº de ref. del artículo: V9780898713411
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: New. Nº de ref. del artículo: 1514175-n
Cantidad disponible: 3 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 1514175
Cantidad disponible: 3 disponibles
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
Condición: New. 1987. Paperback. . . . . . Books ship from the US and Ireland. Nº de ref. del artículo: V9780898713411
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Librería: Revaluation Books, Exeter, Reino Unido
Paperback. Condición: Brand New. illustrated edition. 236 pages. 9.25x6.25x0.50 inches. In Stock. Nº de ref. del artículo: __0898713412
Cantidad disponible: 2 disponibles
Librería: Rarewaves.com UK, London, Reino Unido
Paperback. Condición: New. This reprint of the 1969 book of the same name is a concise, rigorous, yet accessible account of the fundamentals of constrained optimization theory. Many problems arising in diverse fields such as machine learning, medicine, chemical engineering, structural design, and airline scheduling can be reduced to a constrained optimization problem. This book provides readers with the fundamentals needed to study and solve such problems.Beginning with a chapter on linear inequalities and theorems of the alternative, basics of convex sets and separation theorems are then derived based on these theorems. This is followed by a chapter on convex functions that includes theorems of the alternative for such functions. These results are used in obtaining the saddlepoint optimality conditions of nonlinear programming without differentiability assumptions. Properties of differentiable convex functions are derived and then used in two key chapters of the book, one on optimality conditions for differentiable nonlinear programs and one on duality in nonlinear programming. Generalizations of convex functions to pseudoconvex and quasiconvex functions are given and then used to obtain generalized optimality conditions and duality results in the presence of nonlinear equality constraints.The book has four useful self-contained appendices on vectors and matrices, topological properties of n-dimensional real space, continuity and minimization, and differentiable functions. Nº de ref. del artículo: LU-9780898713411
Cantidad disponible: 1 disponibles