MATH 7237 — Theory of Optimization
4 semester hoursGraduateLectureusually offered: falltypical days: M/WBostonTraditional
Focuses on the rigorous mathematical theory pertaining to finite-dimensional optimization including convex analysis, optimality conditions, Lagrangean duality, and convergence rates of optimization algorithms. Topics include convex sets, cones, polar cones, dual cones, extreme points, polyhedra, convex functions, epigraphs, subgradients, convex conjugation, Fenchel-Moreau theorem, necessary and sufficient conditions for optimality, tangent cones, constraint qualification, Slater’s condition, Karush-Kuhn-Tucker conditions, Lagrange multipliers, primal problems and dual problems, semidefinite programming, Farkas’ lemma, theorems of the alternative, gradient descent, Newton’s method, and convergence rates.
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Fall 2025 | 1 | 18 | 21 | 86% | 3.0 |
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 100% · T 0% · W 100% · Th 0% · F 0%
Common patterns: MW (100% of sections) — in patterns, R means Thursday
Professors
Fall
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