Focusing on the intersection of operations research, computer science, and applied mathematics, this book delves into combinatorial optimization, highlighting its significance in diverse applications such as network design, scheduling, and computational biology. It traces the historical roots of the field to linear programming, noting key advancements like the ellipsoid method and interior point approaches that have revolutionized problem-solving. The text emphasizes the commonality of discrete problems and their connection to linear programming, including the development of approximation algorithms for NP-hard issues.
