Interior Point Methods Mathematical (44 results)

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Softcover. Condition: gut. Lineare Programmung Informatik Mathematik mathematics computer science "An innovative, attractive introduction to linear programming " American Mathematical Monthly For upper-division/graduate courses in operations research/management science, mathematics, and computer science, this text covers basic theory, selected applications, network flow problems, and advanced techniques. A masterpiece on Linear Programming. Although it does not contain Interior Point Methods developed subsequently, it's always the first book I refer to, whenever I have any questions on Linear Programming. Strongly Recommended. This book is a good introduction to linear programming. And very readable. It also serves as a good reference. For a more advanced text and non-linear programming topics, look at Nash and Sofer. Informatik Mathematik I've been teaching a linear programming course at the advanced undergraduate level out of this book for the last 12 years. I'm still happy with Chvatal's book and haven't found anything better. Prerequisites for this book include some background in linear algebra (the typical sophomore level introduction to linear algebra is enough), and some experience with proof based mathematics. Because the subject does not involve the difficult concepts of analysis, it (much like number theory) makes a good subject for students to study as they are developing proof writing skills. The first 10 chapters of the book present the simplex method, the revised simplex method, duality theory, and sensitivity analysis. This material can easily be covered in 10 weeks. The remaining chapters of the book are largely independent, mostly focused on various applications of linear programming and specialization of the simplex method to network flow problems. Chvatal presents the simplex method and many of its applications from a mathematical point of view. He states and proves theorems, but also provides plenty of motivation. Students who make an effort do develop more mathematical maturity from working through this book. Chvatal also presents the material from a computational and algorithmic point of view. One of the major points of the book is that the author prefers to use algorithmic proofs. For example, the proof that every standard form LP is either infeasibile, unbounded, or has an optimal BFS is built on the simplex method- Since the algorithm terminates in one of these three states, and can't go into an infinite loop, these are the only possibilities. Another particular strength of the book is in the presentation of duality theory. The explanation is simply very clear and intuitive. The one glaring weakness of the book is that it doesn't contain any discussion of interior point methods for linear programming. Since the book was published in the mid 1980's, this is not surprising. In my course, I supplement Chvatal's book with my own lecture notes on interior point methods. Zusatzinfo 98ill. Sprache englisch Maße 150 x 230 mm Mathematik Informatik Mathe ISBN-10 0-7167-1195-8 / 0716711958 ISBN-13 978-0-7167-1195-7 / 9780716711957 In englischer Sprache. 478 pages. 16,7 x 2,4 x 23,4 cm Auflage: Original Spelli. (15. September 1983).

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The starting point of this volume was a conference entitled 'Progress in Mathematical Programming,' held at the Asilomar Conference Center in Pacific Grove, California, March 1-4, 1987. The main topic of the conference was developments in the theory and practice of linear programming since Karmarkar's algorithm. There were thirty presentations and approximately fifty people attended. Presentations included new algorithms, new analyses of algorithms, reports on computational experience, and some other topics related to the practice of mathematical programming. Interestingly, most of the progress reported at the conference was on the theoretical side. Several new polynomial algorithms for linear program ming were presented (Barnes-Chopra-Jensen, Goldfarb-Mehrotra, Gonzaga, Kojima-Mizuno-Yoshise, Renegar, Todd, Vaidya, and Ye). Other algorithms presented were by Betke-Gritzmann, Blum, Gill-Murray-Saunders-Wright, Nazareth, Vial, and Zikan-Cottle. Efforts in the theoretical analysis of algo rithms were also reported (Anstreicher, Bayer-Lagarias, Imai, Lagarias, Megiddo-Shub, Lagarias, Smale, and Vanderbei). Computational experiences were reported by Lustig, Tomlin, Todd, Tone, Ye, and Zikan-Cottle. Of special interest, although not in the main direction discussed at the conference, was the report by Rinaldi on the practical solution of some large traveling salesman problems. At the time of the conference, it was still not clear whether the new algorithms developed since Karmarkar's algorithm would replace the simplex method in practice. Alan Hoffman presented results on conditions under which linear programming problems can be solved by greedy algorithms.

Taschenbuch. Condition: Neu. Progress in Mathematical Programming | Interior-Point and Related Methods | Nimrod Megiddo | Taschenbuch | x | Englisch | 2011 | Springer | EAN 9781461396192 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Condition: 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.

Softcover. Condition: gut. Lineare Programmung Informatik Mathematik mathematics computer science "An innovative, attractive introduction to linear programming " American Mathematical Monthly For upper-division/graduate courses in operations research/management science, mathematics, and computer science, this text covers basic theory, selected applications, network flow problems, and advanced techniques. A masterpiece on Linear Programming. Although it does not contain Interior Point Methods developed subsequently, it's always the first book I refer to, whenever I have any questions on Linear Programming. Strongly Recommended. This book is a good introduction to linear programming. And very readable. It also serves as a good reference. For a more advanced text and non-linear programming topics, look at Nash and Sofer. Informatik Mathematik I've been teaching a linear programming course at the advanced undergraduate level out of this book for the last 12 years. I'm still happy with Chvatal's book and haven't found anything better. Prerequisites for this book include some background in linear algebra (the typical sophomore level introduction to linear algebra is enough), and some experience with proof based mathematics. Because the subject does not involve the difficult concepts of analysis, it (much like number theory) makes a good subject for students to study as they are developing proof writing skills. The first 10 chapters of the book present the simplex method, the revised simplex method, duality theory, and sensitivity analysis. This material can easily be covered in 10 weeks. The remaining chapters of the book are largely independent, mostly focused on various applications of linear programming and specialization of the simplex method to network flow problems. Chvatal presents the simplex method and many of its applications from a mathematical point of view. He states and proves theorems, but also provides plenty of motivation. Students who make an effort do develop more mathematical maturity from working through this book. Chvatal also presents the material from a computational and algorithmic point of view. One of the major points of the book is that the author prefers to use algorithmic proofs. For example, the proof that every standard form LP is either infeasibile, unbounded, or has an optimal BFS is built on the simplex method- Since the algorithm terminates in one of these three states, and can't go into an infinite loop, these are the only possibilities. Another particular strength of the book is in the presentation of duality theory. The explanation is simply very clear and intuitive. The one glaring weakness of the book is that it doesn't contain any discussion of interior point methods for linear programming. Since the book was published in the mid 1980's, this is not surprising. In my course, I supplement Chvatal's book with my own lecture notes on interior point methods. ISBN-10 0-7167-1587-2 / 0716715872 ISBN-13 978-0-7167-1587-0 / 9780716715870 In englischer Sprache. 478 pages. 16,7 x 2,4 x 23,4 cm Auflage: Original Spelli. (15. September 1983).

Ed. MPS-SIAM - 2001, Series on Optimization, in-8, broché, 117 pages Bon état.

Hardcover Sep 30, 1996. Condition: 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+].

Hardcover Sep 30, 1996. Condition: 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+].

Hardcover. Condition: gut. Lineare Programmung Informatik Mathematik mathematics computer science "An innovative, attractive introduction to linear programming " American Mathematical Monthly For upper-division/graduate courses in operations research/management science, mathematics, and computer science, this text covers basic theory, selected applications, network flow problems, and advanced techniques. A masterpiece on Linear Programming. Although it does not contain Interior Point Methods developed subsequently, it's always the first book I refer to, whenever I have any questions on Linear Programming. Strongly Recommended. This book is a good introduction to linear programming. And very readable. It also serves as a good reference. For a more advanced text and non-linear programming topics, look at Nash and Sofer. Informatik Mathematik I've been teaching a linear programming course at the advanced undergraduate level out of this book for the last 12 years. I'm still happy with Chvatal's book and haven't found anything better. Prerequisites for this book include some background in linear algebra (the typical sophomore level introduction to linear algebra is enough), and some experience with proof based mathematics. Because the subject does not involve the difficult concepts of analysis, it (much like number theory) makes a good subject for students to study as they are developing proof writing skills. The first 10 chapters of the book present the simplex method, the revised simplex method, duality theory, and sensitivity analysis. This material can easily be covered in 10 weeks. The remaining chapters of the book are largely independent, mostly focused on various applications of linear programming and specialization of the simplex method to network flow problems. Chvatal presents the simplex method and many of its applications from a mathematical point of view. He states and proves theorems, but also provides plenty of motivation. Students who make an effort do develop more mathematical maturity from working through this book. Chvatal also presents the material from a computational and algorithmic point of view. One of the major points of the book is that the author prefers to use algorithmic proofs. For example, the proof that every standard form LP is either infeasibile, unbounded, or has an optimal BFS is built on the simplex method- Since the algorithm terminates in one of these three states, and can't go into an infinite loop, these are the only possibilities. Another particular strength of the book is in the presentation of duality theory. The explanation is simply very clear and intuitive. The one glaring weakness of the book is that it doesn't contain any discussion of interior point methods for linear programming. Since the book was published in the mid 1980's, this is not surprising. In my course, I supplement Chvatal's book with my own lecture notes on interior point methods. Zusatzinfo 98ill. Sprache englisch Maße 150 x 230 mm Mathematik Informatik Mathe ISBN-10 0-7167-1195-8 / 0716711958 ISBN-13 978-0-7167-1195-7 / 9780716711957 In englischer Sprache. 478 pages. 16,7 x 2,4 x 23,4 cm Auflage: Original Spelli. (15. September 1983).

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Condition: 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 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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