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Combinatorial Optimization: Algorithms and Complexity (Dover Books on Computer Science)

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Clearly written graduate-level text considers the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NP-complete problems, more. "Mathematicians wishing a self-contained introduction need look no further." Clearly written graduate-level text considers the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NP-complete problems, more. "Mathematicians wishing a self-contained introduction need look no further." — American Mathematical Monthly. 1982 edition..


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Clearly written graduate-level text considers the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NP-complete problems, more. "Mathematicians wishing a self-contained introduction need look no further." Clearly written graduate-level text considers the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NP-complete problems, more. "Mathematicians wishing a self-contained introduction need look no further." — American Mathematical Monthly. 1982 edition..

30 review for Combinatorial Optimization: Algorithms and Complexity (Dover Books on Computer Science)

  1. 5 out of 5

    Nick Black

    An immediate classic and still the basic textbook in its field, you simply will not find a better deal than this $19.95 gift to the combinatorially-minded public from the wonderful folk at Dover Mathematical Publishing ([sniff] god bless and keep those men!).

  2. 4 out of 5

    Bernhard Geiger

    First: I'm no expert in optimization, and this might be one reason why I did not like this book that much. I also skipped a good portion of the book, which I considered not being relevant for my work. One of the main drawbacks of this book is that, although the title speaks of combinatorial optimization, the topic is (integer) linear programming. I would have preferred at least a few chapters on nonlinear integer problems. Chapter 2 concerned the simplex algorithm and was a pleasure to read. Chap First: I'm no expert in optimization, and this might be one reason why I did not like this book that much. I also skipped a good portion of the book, which I considered not being relevant for my work. One of the main drawbacks of this book is that, although the title speaks of combinatorial optimization, the topic is (integer) linear programming. I would have preferred at least a few chapters on nonlinear integer problems. Chapter 2 concerned the simplex algorithm and was a pleasure to read. Chapter 3 dealt with the dual of a program, a concept which still escapes my understanding. I skipped Chapters 4-7 which concern the primal-dual algorithm and implementations (nowadays, I think LPs are solved using computer software). After a brief introduction to Landau's notation and complexity in Chapter 8, there are again three chapters devoted only to algorithms. I would have preferred a more rigorous treatment of matroids in Chapter 12; the chapters on integer LPs and the cutting-plane algorithm were excellently written. Chapters 15 and 16 introduce NP-complete problems, and Chapter 17 suggests approximative algorithms. Very interesting is again Chapter 18, which is almost exclusively devoted to the branch-and-bound method. Chapter 19, on local search, is exemplary for the overall appearance of the book: It is so full of examples that the big picture does not come across.

  3. 5 out of 5

    dead letter office

    a $19 classic text on combinatorial optimization. thank you dover.

  4. 5 out of 5

    Sabrish

    A bit shocked when I read KKT sufficiency criterion being applied to concave constrained NL problem...a bit rattled by this...I think this is a more computer science oriented book than a rigorous mathematical text

  5. 4 out of 5

    DJ

    another gem from Dover

  6. 5 out of 5

    Brandon

  7. 5 out of 5

    Taran Rampersad

  8. 5 out of 5

    Hal Rogers

  9. 5 out of 5

    Paul Harrington

  10. 4 out of 5

    John

  11. 4 out of 5

    Sravani Perumalla

  12. 4 out of 5

    Subhajit Das

  13. 5 out of 5

    Marie Sha

  14. 4 out of 5

    Fanchao MENG

  15. 5 out of 5

    Shivani

  16. 4 out of 5

    Leo

  17. 5 out of 5

    Njorilo

  18. 5 out of 5

    Hari

  19. 4 out of 5

    Perfect Score

  20. 4 out of 5

    Jovany Agathe

  21. 5 out of 5

    Ozan Erdem

  22. 5 out of 5

    Brad

  23. 5 out of 5

    Cvfsdeaws

  24. 5 out of 5

    Tony

  25. 4 out of 5

    Jerry Kam

  26. 5 out of 5

    Ariel Schvartzman

  27. 4 out of 5

    Josh Clark

  28. 4 out of 5

    Nina Šmalcelj

  29. 4 out of 5

    Thang

  30. 4 out of 5

    Jeremiah Dunham

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