MATH 7234 — Optimization and Complexity

4 semester hoursGraduateLectureusually offered: fall, springtypical days: T/ThBostonTraditional

Offers theory and methods of maximizing and minimizing solutions to various types of problems. Studies combinatorial problems including mixed integer programming problems (MIP); pure integer programming problems (IP); Boolean programming problems; and linear programming problems (LP). Topics include convex subsets and polyhedral subsets of n-space; relationship between an LP problem and its dual LP problem, and the duality theorem; simplex algorithm, and Kuhn-Tucker conditions for optimality for nonlinear functions; and network problems, such as minimum cost and maximum flow-minimum cut. Also may cover complexity of algorithms; problem classes P (problems with polynomial-time algorithms) and NP (problems with nondeterministic polynomial-time algorithms); Turing machines; and NP-completeness of traveling salesman problem and other well-known problems.

Offering history

TermSectionsEnrolledCapacityFullOpen seats/section
Fall 20231112055%9.0
Summer A 20241113037%19.0
Fall 2024132015%17.0
Spring 20251133043%17.0
Spring 20261193063%11.0

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 44% · T 56% · W 44% · Th 75% · F 0%

Common patterns: TR (56% of sections), MW (25% of sections), MWR (19% of sections) — in patterns, R means Thursday

Professors

Fall

Spring

Summer A

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