Modeling and Methods in Optimization

Where IE 202 left you with continuous linear programs, this course is about what happens when decisions are discrete, structured as networks, or built up stage by stage — the regime where most real planning problems actually live. You'll formulate integer programs (with the modeling tricks that make them solvable), run branch-and-bound and cutting planes by hand before letting a solver do it, work through shortest-path and max-flow algorithms, and design heuristics when exact methods give up. It's the bridge between LP theory and the harder combinatorial models you'll see in scheduling, logistics, and the senior design project.