Applied Optimization

The course focuses on the modeling and solution of practical optimization problems. It covers formulations based on integer and nonlinear optimization, solution approaches based on large-scale optimization, and algorithmic design and implementation. Topics include set covering formulations, Lagrangean relaxation, Benders decomposition, column generation, branch-and-price, nonlinear programming, and metaheuristics. Possible applications areas include bin packing, routing, scheduling, and logistics planning. Priority may be given to Management Sciences students.