AuthorKarloff, Howard. author
TitleLinear Programming [electronic resource] / by Howard Karloff
ImprintBoston, MA : Birkhรคuser Boston, 1991
Edition 1
Connect tohttp://dx.doi.org/10.1007/978-0-8176-4844-2
Descript VIII, 144 p. 6 illus. online resource

SUMMARY

To this reviewer's knowledge, this is the first book accessible to the upper division undergraduate or beginning graduate student that surveys linear programming from the Simplex Methodโฆvia the Ellipsoid algorithm to Karmarkar's algorithm. Moreover, its point of view is algorithmic and thus it provides both a history and a case history of work in complexity theory. The presentation is admirable; Karloff's style is informal (even humorous at times) without sacrificing anything necessary for understanding. Diagrams (including horizontal brackets that group terms) aid in providing clarity. The end-of-chapter notes are helpful...Recommended highly for acquisition, since it is not only a textbook, but can also be used for independent reading and study. โChoice Reviews The reader will be well served by reading the monograph from cover to cover. The author succeeds in providing a concise, readable, understandable introduction to modern linear programming. โMathematics of Computing This is a textbook intended for advanced undergraduate or graduate students. It contains both theory and computational practice. After preliminary discussion of linear algebra and geometry, it describes the simplex algorithm, duality, the ellipsoid algorithm (Khachiyan's algorithm) and Karmarkar's algorithm. โZentralblatt Math The exposition is clear and elementary; it also contains many exercises and illustrations. โMathematical Reviews A self-contained, concise mathematical introduction to the theory of linear programming. โJournal of Economic Literature


CONTENT

The Basics -- The Simplex Algorithm -- Duality -- The Ellipsoid Algorithm -- Karmarkar's Algorithm


SUBJECT

  1. Computer science
  2. Computer programming
  3. Programming languages (Electronic computers)
  4. Algorithms
  5. Computer science -- Mathematics
  6. Applied mathematics
  7. Engineering mathematics
  8. Computer mathematics
  9. Computer Science
  10. Programming Techniques
  11. Applications of Mathematics
  12. Programming Languages
  13. Compilers
  14. Interpreters
  15. Math Applications in Computer Science
  16. Computational Mathematics and Numerical Analysis
  17. Algorithm Analysis and Problem Complexity