A First Course in Combinatorial Optimization is a text for a one-semester introductory graduate-level course for students of operations research, mathematics, and computer science. It is a self-contained treatment of the subject, requiring only some mathematical maturity. Topics include: linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. Central to the exposition is the polyhedral viewpoint, which is the key principle underlying the successful integer-programming approach to combinatorial-optimization problems. Another key unifying topic is matroids. The author does not dwell on data structures and implementation details, preferring to focus on the key mathematical ideas that lead to useful models and algorithms. Problems and exercises are included throughout as well as references for further study.
Rezensionen / Stimmen
'The author, with his light but rigorous mathematical writing style, takes delight in revealing the stars of combinatorial optimization. This is an excellent teaching book; I recommend it highly.' International Statistical Institute
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Produkt-Hinweis
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Worked examples or Exercises
Maße
Höhe: 229 mm
Breite: 152 mm
Dicke: 14 mm
Gewicht
ISBN-13
978-0-521-01012-2 (9780521010122)
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Schweitzer Klassifikation
Jon Lee is a passionate outdoorsman with 20 years of guiding experience, helping novices and experts alike thrive in the realm of angling and hunting. From the vast landscapes of Alaska to the picturesque waters of Key West, he's tackled it all: fly fishing and big game archery being his specialties. Based in Michigan, Jon is perpetually on the hunt for the next great adventure, channeling his experiences into captivating short stories that resonate with readers far and wide.
Autor*in
IBM T J Watson Research Center, New York
Introduction; Polytopes and linear programming; 1. Matroids and the greedy algorithm; 2. Minimum-weight dipaths; 3. Matroid intersection; 4. Matching; 5. Flows and cuts; 6. Cutting planes; 7. Branch-&-bound; 8. Optimizing submodular functions; Appendix.