Linear Programming – Optimization, Duality & Applications | Chapter 29 in Introduction to Algorithms
Linear Programming – Optimization, Duality & Applications | Chapter 29 in Introduction to Algorithms Chapter 29 of Introduction to Algorithms presents a comprehensive foundation in linear programming (LP) , a powerful optimization tool widely used in computer science, operations research, and economics. The chapter walks through how to formulate LP problems, introduces geometric intuition, and compares algorithmic approaches like the simplex method , ellipsoid algorithm , and interior-point methods . It also explores advanced topics such as duality theory and integer linear programming (ILP) . Watch the full video above for a visual summary of Chapter 29, and be sure to subscribe to Last Minute Lecture for more high-quality textbook breakdowns every week. What Is Linear Programming? Linear programming is a method for optimizing a linear objective function subject to linear equality and inequality constraints . A typical LP seeks to maximize or minimize an expression...