Benders Decomposition solves mixed-integer programs by decomposing into master problem (integer variables) and subproblem (continuous variables). For each master solution, the subproblem checks feasibility and optimality, generating cuts added to the master problem. Types of cuts: (1) Optimality cuts - improve objective function bounds; (2) Feasibility cuts - eliminate infeasible master solutions. The algorithm iterates until convergence. Benders is particularly effective for problems with complicating integer variables - when fixing integers, the remaining problem is easy to solve. Modern accelerations include: multi-cut strategies, cut strengthening, and combinatorial Benders. Applications: facility location, network design, production planning, and two-stage stochastic programming (L-shaped method).