CME310

Download as PDF

Combinatorial Optimization

Course Description

Algorithms, algorithmic paradigms, and algorithmic tools for provably solving combinatorial optimization problems. Emphasis on graph optimization and discussion of approaches based on linear programming and continuous optimization. Potential optimization problems include both polynomial time solve-able problems, e.g., maximum flow, minimum cost flow, matching, assignment, minimum cut, matroid optimization, submodular function minimization, and NP-hard problems, e.g., Steiner trees, traveling salesperson, maximum cut. Potential paradigms and tools include: linear programming, multiplicative weight update method, algebraic methods, and spectral methods. Prerequisite: 161 or equivalent.

Cross Listed Courses

Grading Basis

ROP - Letter or Credit/No Credit

Min

3

Max

3

Course Repeatable for Degree Credit?

No

Course Component

Lecture

Enrollment Optional?

No

Does this course satisfy the University Language Requirement?

No

Schedule

Expand all
No Sections Found

Programs

CME310 is a completion requirement for:
  • (from the following course set: )
  • (from the following course set: )