9780792342014 - interior point methods of mathematical programming: 5 (applied optimization, 5) de terlaky, tamás (14 resultados)
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Librería: Anybook.com, Lincoln, Reino UnidoAnybook.com
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EUR 89,40
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Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1200grams, ISBN:9780792342014.
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Librería: Librairie Parrêsia, Figeac, , FranciaLibrairie Parrêsia
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EUR 120,00
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Hardcover Sep 30, 1996. Condición: Used: Very Good. Interior Point Methods in Mathematical Programming | T. Terlaky | Kluwer Academic, 1996, in-8 cartonnage éditeur, 528 pages. Couverture très légèrement passée. Dos solide. Intérieur frais. Exemplaire de bibliothèque : petit code barre en pied de 1re de couv., cotation au dos, r…ares et discrets petits tampons à l'intérieur de l'ouvrage. Bon exemplaire. [BT35+].
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Librería: Librairie Parrêsia, Figeac, , FranciaLibrairie Parrêsia
Contactar con el vendedorVendedor de 4 estrellasCondición: Usado - Bueno
EUR 120,00
Envío por EUR 32,50Se envía de Francia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover Sep 30, 1996. Condición: Used: Very Good. Interior Point Methods in Mathematical Programming | T. Terlaky | Kluwer Academic, 1996, in-8 cartonnage éditeur, 528 pages. Couverture très légèrement passée. Dos solide. Intérieur frais. Exemplaire de bibliothèque : petit code barre en pied de 1re de couv., cotation au dos, r…ares et discrets petits tampons à l'intérieur de l'ouvrage. Bon exemplaire. [BT35+].
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 310,79
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Condición: New. In.
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Librería: moluna, Greven, , Alemaniamoluna
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EUR 267,86
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Gebunden. Condición: New.
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Librería: Buchpark, Trebbin, , AlemaniaBuchpark
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EUR 215,65
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Condición: Gut. Zustand: Gut | Seiten: 556 | Sprache: Englisch | Produktart: Bücher | One has to make everything as simple as possible but, never more simple. Albert Einstein Discovery consists of seeing what every body has seen and thinking what nobody has thought. Albert S. ent_Gyorgy; The primary goal of this book is to prov…ide an introduction to the theory of Interior Point Methods (IPMs) in Mathematical Programming. At the same time, we try to present a quick overview of the impact of extensions of IPMs on smooth nonlinear optimization and to demonstrate the potential of IPMs for solving difficult practical problems. The Simplex Method has dominated the theory and practice of mathematical pro gramming since 1947 when Dantzig discovered it. In the fifties and sixties several attempts were made to develop alternative solution methods. At that time the prin cipal base of interior point methods was also developed, for example in the work of Frisch (1955), Caroll (1961), Huard (1967), Fiacco and McCormick (1968) and Dikin (1967). In 1972 Klee and Minty made explicit that in the worst case some variants of the simplex method may require an exponential amount of work to solve Linear Programming (LP) problems. This was at the time when complexity theory became a topic of great interest. People started to classify mathematical programming prob lems as efficiently (in polynomial time) solvable and as difficult (NP-hard) problems. For a while it remained open whether LP was solvable in polynomial time or not. The break-through resolution ofthis problem was obtained by Khachijan (1989).
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 332,62
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Condición: New.
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Librería: Buchpark, Trebbin, , AlemaniaBuchpark
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EUR 222,12
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Condición: Sehr gut. Zustand: Sehr gut | Seiten: 556 | Sprache: Englisch | Produktart: Bücher | One has to make everything as simple as possible but, never more simple. Albert Einstein Discovery consists of seeing what every body has seen and thinking what nobody has thought. Albert S. ent_Gyorgy; The primary goal of this book…is to provide an introduction to the theory of Interior Point Methods (IPMs) in Mathematical Programming. At the same time, we try to present a quick overview of the impact of extensions of IPMs on smooth nonlinear optimization and to demonstrate the potential of IPMs for solving difficult practical problems. The Simplex Method has dominated the theory and practice of mathematical pro gramming since 1947 when Dantzig discovered it. In the fifties and sixties several attempts were made to develop alternative solution methods. At that time the prin cipal base of interior point methods was also developed, for example in the work of Frisch (1955), Caroll (1961), Huard (1967), Fiacco and McCormick (1968) and Dikin (1967). In 1972 Klee and Minty made explicit that in the worst case some variants of the simplex method may require an exponential amount of work to solve Linear Programming (LP) problems. This was at the time when complexity theory became a topic of great interest. People started to classify mathematical programming prob lems as efficiently (in polynomial time) solvable and as difficult (NP-hard) problems. For a while it remained open whether LP was solvable in polynomial time or not. The break-through resolution ofthis problem was obtained by Khachijan (1989).
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 359,77
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Condición: As New. Unread book in perfect condition.
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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EUR 383,59
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Condición: New. Offers an overview of the research in interior point methods. This book gives an overview of basic variants of interior point algorithms for linear programming. It also deals with nonlinear programming. It is useful for researchers and graduate students in mathematical programming, operations research, management… science, and combinatorics. Editor(s): Terlaky, Tamas. Series: Applied Optimization. Num Pages: 552 pages, biography. BIC Classification: PBT; PBW; UM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 30. Weight in Grams: 951. . 1996. Hardback. . . . .
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 333,77
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - One has to make everything as simple as possible but, never more simple. Albert Einstein Discovery consists of seeing what every body has seen and thinking what nobody has thought. Albert S. ent_Gyorgy; The primary goal of this book is to provide an intro…duction to the theory of Interior Point Methods (IPMs) in Mathematical Programming. At the same time, we try to present a quick overview of the impact of extensions of IPMs on smooth nonlinear optimization and to demonstrate the potential of IPMs for solving difficult practical problems. The Simplex Method has dominated the theory and practice of mathematical pro gramming since 1947 when Dantzig discovered it. In the fifties and sixties several attempts were made to develop alternative solution methods. At that time the prin cipal base of interior point methods was also developed, for example in the work of Frisch (1955), Caroll (1961), Huard (1967), Fiacco and McCormick (1968) and Dikin (1967). In 1972 Klee and Minty made explicit that in the worst case some variants of the simplex method may require an exponential amount of work to solve Linear Programming (LP) problems. This was at the time when complexity theory became a topic of great interest. People started to classify mathematical programming prob lems as efficiently (in polynomial time) solvable and as difficult (NP-hard) problems. For a while it remained open whether LP was solvable in polynomial time or not. The break-through resolution ofthis problem was obtained by Khachijan (1989).
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Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 480,78
Envío por EUR 9,06Se envía dentro de Estados Unidos de AmericaCantidad disponible: 15 disponibles
Condición: New. Offers an overview of the research in interior point methods. This book gives an overview of basic variants of interior point algorithms for linear programming. It also deals with nonlinear programming. It is useful for researchers and graduate students in mathematical programming, operations research, management… science, and combinatorics. Editor(s): Terlaky, Tamas. Series: Applied Optimization. Num Pages: 552 pages, biography. BIC Classification: PBT; PBW; UM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 30. Weight in Grams: 951. . 1996. Hardback. . . . . Books ship from the US and Ireland.
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 320,99
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -One has to make everything as simple as possible but, never more simple. Albert Einstein Discovery consists of seeing what every body has seen and thinking what nobody has thought. Albert S. ent_Gyorgy; The primary goal of this book is to prov…ide an introduction to the theory of Interior Point Methods (IPMs) in Mathematical Programming. At the same time, we try to present a quick overview of the impact of extensions of IPMs on smooth nonlinear optimization and to demonstrate the potential of IPMs for solving difficult practical problems. The Simplex Method has dominated the theory and practice of mathematical pro gramming since 1947 when Dantzig discovered it. In the fifties and sixties several attempts were made to develop alternative solution methods. At that time the prin cipal base of interior point methods was also developed, for example in the work of Frisch (1955), Caroll (1961), Huard (1967), Fiacco and McCormick (1968) and Dikin (1967). In 1972 Klee and Minty made explicit that in the worst case some variants of the simplex method may require an exponential amount of work to solve Linear Programming (LP) problems. This was at the time when complexity theory became a topic of great interest. People started to classify mathematical programming prob lems as efficiently (in polynomial time) solvable and as difficult (NP-hard) problems. For a while it remained open whether LP was solvable in polynomial time or not. The break-through resolution ofthis problem was obtained by Khachijan (1989).Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 556 pp. Englisch.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , AlemaniaBuchWeltWeit Ludwig Meier e.K.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 362,73
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -One has to make everything as simple as possible but, never more simple. Albert Einstein Discovery consists of seeing what every body has seen and thinking what nobody has thought. Albert S. ent_Gyorgy; The primary goal of this book is to…provide an introduction to the theory of Interior Point Methods (IPMs) in Mathematical Programming. At the same time, we try to present a quick overview of the impact of extensions of IPMs on smooth nonlinear optimization and to demonstrate the potential of IPMs for solving difficult practical problems. The Simplex Method has dominated the theory and practice of mathematical pro gramming since 1947 when Dantzig discovered it. In the fifties and sixties several attempts were made to develop alternative solution methods. At that time the prin cipal base of interior point methods was also developed, for example in the work of Frisch (1955), Caroll (1961), Huard (1967), Fiacco and McCormick (1968) and Dikin (1967). In 1972 Klee and Minty made explicit that in the worst case some variants of the simplex method may require an exponential amount of work to solve Linear Programming (LP) problems. This was at the time when complexity theory became a topic of great interest. People started to classify mathematical programming prob lems as efficiently (in polynomial time) solvable and as difficult (NP-hard) problems. For a while it remained open whether LP was solvable in polynomial time or not. The break-through resolution ofthis problem was obtained by Khachijan (1989). 556 pp. Englisch.
