MATH 7207 — Algorithms for Optimization
4 semester hoursGraduateLecturetypical days: T/ThBostonTraditional
Covers algorithms used to solve optimization problems, specifically algorithms used to optimize a set of continuous design variables. Presents classic algorithms such as gradient descent, Newton’s method, simulated annealing, the simplex method, and others. Studies algorithms for both unconstrained and constrained optimization. Discusses optimization of both convex and nonconvex objective functions. Emphasizes hands-on and practical implementation of the algorithms presented by writing computer programs. Uses applications from business and industry to illustrate how the algorithms work and when they should be applied.
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Fall 2024 | 1 | 25 | 30 | 83% | 5.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 0% · T 100% · W 0% · Th 100% · F 0%
Common patterns: TR (100% of sections) — in patterns, R means Thursday
Professors
Fall
- Stuart Brorson (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (MATH course descriptions) · Student reviews on RateMyHusky · All MATH courses · Plan it at numap.app