Mixed-Integer Optimization Purpose Provides capabilities for formulating and solving mixed-integer linear and nonlinear programming problems. Capabilities - Branch and bound/cut algorithms - MIP formulation techniques - Indicator constraints - Big-M reformulations - Lazy constraints - Solution pool generation Usage Guidelines 1. Formulation : Use tight formulations with valid inequalities 2. Big-M Selection : Choose appropriate Big-M values 3. Branching : Configure branching priorities 4. Solution Pool : Generate diverse feasible solutions Tools/Libraries - Gurobi - CPLEX - SCIP - CBC ---