The Cutting Stock Problem minimizes waste when cutting raw materials (rolls, sheets) into smaller pieces. Classical formulation has exponential columns (cutting patterns). Column generation approach: (1) Master Problem - selects patterns minimizing total rolls used; (2) Pricing Subproblem - finds new pattern (knapsack problem) with negative reduced cost. The algorithm generates only needed patterns iteratively. Gilmore-Gomory method applies this framework to solve large-scale instances. Extensions handle: multiple stock sizes, two-dimensional cutting, and trim loss minimization. Applications: paper industry, steel manufacturing, glass cutting, and textile production. This problem pioneered column generation methodology, demonstrating effectiveness for problems with many variables.