This self-contained beginning graduate text covers linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. A First Course in Combinatorial Optimization is a self-contained text for a one-semester introductory graduate-level course for students of operations research, mathematics, and computer science. The author focuses on the key mathematical ideas that lead to useful models and algorithms rather than on data structures and implementation details. The viewpoint is polyhedral, and the author also uses matroids as a unifying idea.Topics include linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. Problems and exercises are included throughout as well as references for further study. A First Course in Combinatorial Optimization is a self-contained text for a one-semester introductory graduate-level course for students of operations research, mathematics, and computer science. The author focuses on the key mathematical ideas that lead to useful models and algorithms rather than on data structures and implementation details. The viewpoint is polyhedral, and the author also uses matroids as a unifying idea.Topics include linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. Problems and exercises are included throughout as well as references for further study.Jon Lee focuses on key mathematical ideas leading to useful models and algorithms, rather than on data structures and implementation details, in this introductory graduate-level text for students of operations research, mathematics, and computer science. The viewpoint is polyhedral, and Lee also uses matroids as a unifying idea. Topics include linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. Problems and exercises are included throughout as well as references for further stulCZ