ISBN: 9780792342014 - interior point methods in mathematical programming: 5 (10 risultati)

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  • Lingua: Inglese

    Editore: Springer, 1996

    0792342011 / 9780792342014

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    Da: Librairie Parrêsia, Figeac, FranciaLibrairie Parrêsia

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    Hardcover Sep 30, 1996. Condizione: 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, rares et discrets petits tampons à l'intérieur de l'ouvrage. Bon exemplaire. [BT35+].…

  • Lingua: Inglese

    Editore: Springer, 1996

    0792342011 / 9780792342014

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    Da: Librairie Parrêsia, Figeac, FranciaLibrairie Parrêsia

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    Condizione: Usato - Molto buono

    EUR 120,00

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    Hardcover Sep 30, 1996. Condizione: 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, rares et discrets petits tampons à l'intérieur de l'ouvrage. Bon exemplaire. [BT35+].…

  • Lingua: Inglese

    Editore: Springer US, 1996

    0792342011 / 9780792342014

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    Da: moluna, Greven, Germaniamoluna

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    EUR 267,86

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    Gebunden. Condizione: New.

  • Lingua: Inglese

    Editore: Springer US, 1996

    0792342011 / 9780792342014

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    Da: Buchpark, Trebbin, GermaniaBuchpark

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    EUR 215,65

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    Condizione: 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). …

  • Lingua: Inglese

    Editore: Springer, 1996

    0792342011 / 9780792342014

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    Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections

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    EUR 352,71

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Kluwer Academic Publishers, 1996

    0792342011 / 9780792342014

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    Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.

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    Condizione: 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. . . . . …

  • Lingua: Inglese

    Editore: Springer US, 1996

    0792342011 / 9780792342014

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 358,67

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    Buch. Condizione: 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 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).…

  • Lingua: Inglese

    Editore: Kluwer Academic Publishers, 1996

    0792342011 / 9780792342014

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    Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore

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    Condizione: 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. …

  • Lingua: Inglese

    Editore: Springer, Springer Sep 1996, 1996

    0792342011 / 9780792342014

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    Buch. Condizione: 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 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).Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 556 pp. Englisch.…

  • Lingua: Inglese

    Editore: Springer US Sep 1996, 1996

    0792342011 / 9780792342014

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 362,73

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    Buch. Condizione: 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.…