Linear Nonlinear Optimization by Igor Griva (16 results)

Condition: New. 2008. 2nd Edition. Hardcover. Flexible graduate textbook that introduces the applications, theory, and algorithms of linear and nonlinear optimization. Num Pages: 764 pages, ill. BIC Classification: PBU. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 261 x 180 x 40. Weight in Grams: 1482. . . . . . …

Condition: Acceptable. Item in acceptable condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.

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Condition: New.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Hardback. Condition: Fair. Introduces the applications, theory, and algorithms of linear and nonlinear optimization, with an emphasis on the practical aspects of the material. A supplemental website offers auxiliary data sets that are necessary for some of the exercises.

Condition: good. Book shows general signs of use and handling. May have light wear on the cover or edges and minimal writing or highlighting. Binding remains tight, and pages are clean and readable.

Condition: New.

Condition: As New. Unread book in perfect condition.

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. Library sticker on front cover. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1600grams, ISBN:9780898716610.…

Hardcover. Condition: Brand New. 2nd edition. 764 pages. 10.20x7.20x1.50 inches. In Stock.

Hardback. Condition: New. Second Edition. Introduces the applications, theory, and algorithms of linear and nonlinear optimization, with an emphasis on the practical aspects of the material. Its unique modular structure provides flexibility to accommodate the varying needs of instructors, students, and practitioners with different levels of sophistication in these topics. The succinct style of this second edition is punctuated with numerous real-life examples and exercises, and the authors include accessible explanations of topics that are not often mentioned in textbooks, such as duality in nonlinear optimization, primal-dual methods for nonlinear optimization, filter methods, and applications such as support-vector machines. Part I provides fundamentals that can be taught in whole or in part at the beginning of a course on either topic and then referred to as needed. Part II on linear programming and Part III on unconstrained optimization can be used together or separately, and Part IV on nonlinear optimization can be taught without having studied the material in Part II. In the preface the authors suggest course outlines that can be adjusted to the requirements of a particular course on both linear and nonlinear optimization, or to separate courses on these topics. Three appendices provide information on linear algebra, other fundamentals, and software packages for optimization problems. A supplemental website offers auxiliary data sets that are necessary for some of the exercises. …

Condition: New. 2008. 2nd Edition. Hardcover. Flexible graduate textbook that introduces the applications, theory, and algorithms of linear and nonlinear optimization. Num Pages: 764 pages, ill. BIC Classification: PBU. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 261 x 180 x 40. Weight in Grams: 1482. . . . . . Books ship from the US and Ireland. …

Condition: New. In English.

Hardback. Condition: New. Second Edition. Introduces the applications, theory, and algorithms of linear and nonlinear optimization, with an emphasis on the practical aspects of the material. Its unique modular structure provides flexibility to accommodate the varying needs of instructors, students, and practitioners with different levels of sophistication in these topics. The succinct style of this second edition is punctuated with numerous real-life examples and exercises, and the authors include accessible explanations of topics that are not often mentioned in textbooks, such as duality in nonlinear optimization, primal-dual methods for nonlinear optimization, filter methods, and applications such as support-vector machines. Part I provides fundamentals that can be taught in whole or in part at the beginning of a course on either topic and then referred to as needed. Part II on linear programming and Part III on unconstrained optimization can be used together or separately, and Part IV on nonlinear optimization can be taught without having studied the material in Part II. In the preface the authors suggest course outlines that can be adjusted to the requirements of a particular course on both linear and nonlinear optimization, or to separate courses on these topics. Three appendices provide information on linear algebra, other fundamentals, and software packages for optimization problems. A supplemental website offers auxiliary data sets that are necessary for some of the exercises. …

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