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Introduction to Linear and Convex Programming [Paperback]

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  • Category: Books (Mathematics)
  • Author:  Cameron, Neil
  • Author:  Cameron, Neil
  • ISBN-10:  0521312078
  • ISBN-10:  0521312078
  • ISBN-13:  9780521312073
  • ISBN-13:  9780521312073
  • Publisher:  Cambridge University Press
  • Publisher:  Cambridge University Press
  • Pages:  160
  • Pages:  160
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-May-1985
  • Pub Date:  01-May-1985
  • SKU:  0521312078-11-MPOD
  • SKU:  0521312078-11-MPOD
  • Item ID: 101276233
  • Seller: ShopSpell
  • Ships in: 2 business days
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  • Delivery by: Jun 30 to Jul 02
  • Notes: Brand New Book. Order Now.
This introduction to optimization emphasizes the need for both a pure and an applied mathematical point of view.This introduction to optimization emphasizes the need for both a pure and an applied mathematical point of view. The author's straightforward, geometrical approach makes this an attractive textbook for undergraduate students of mathematics, engineering, operations research and economics.This introduction to optimization emphasizes the need for both a pure and an applied mathematical point of view. The author's straightforward, geometrical approach makes this an attractive textbook for undergraduate students of mathematics, engineering, operations research and economics.This introduction to optimization emphasizes the need for both a pure and an applied mathematical point of view. Beginning with a chapter on linear algebra and Euclidean geometry, the author then applies this theory with an introduction to linear programming. There follows a discussion of convex analysis, which finds application in non-linear programming. The book ends with an extensive commentary to the exercises that are given at the end of each chapter. The author's straightforward, geometrical approach makes this an attractive textbook for undergraduate students of mathematics, engineering, operations research and economics.Preface; 1. Geometry and linear algebra; 2. Linear programming; 3. Elementary convex analysis; 4. Non-linear programming; Comments on exercises; References; Index.
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