Nonlinear Programming (Classics in Applied Mathematics)

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9780898713411: Nonlinear Programming (Classics in Applied Mathematics)

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.

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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 scheduling can be reduced to a constrained optimization problem. Provides readers with the fundamentals needed to study and solve such problems.

"About this title" may belong to another edition of this title.

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Olvi L. Mangasarian
Published by Society for Industrial and Applied Mathematics
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Olvi L. Mangasarian
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Book Description Society for Industrial Applied Mathematics,U.S., United States, 1994. Paperback. Book Condition: New. 226 x 150 mm. Language: English . Brand New Book. 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. Bookseller Inventory # AAA9780898713411

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Olvi L. Mangasarian
Published by Society for Industrial Applied Mathematics,U.S., United States (1994)
ISBN 10: 0898713412 ISBN 13: 9780898713411
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Book Description Society for Industrial Applied Mathematics,U.S., United States, 1994. Paperback. Book Condition: New. 226 x 150 mm. Language: English . Brand New Book. 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. Bookseller Inventory # AAA9780898713411

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Olvi L. Mangasarian
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Book Description Society for Industrial & Applied, 1995. Paperback. Book Condition: Brand New. illustrated edition. 236 pages. 9.25x6.25x0.50 inches. In Stock. Bookseller Inventory # zk0898713412

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Book Description Society for Industrial Mathematics, 1987. Paperback. Book Condition: New. Bookseller Inventory # SONG0898713412

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