MATH 322
Algorithm Design and Optimization 2
Mathematics
College of Physical and Mathematical Sciences
Course Description
Algorithms used to solve dynamic programming problems and advanced computing problems. Topics include finite-horizon and infinite-horizon dynamic programming, discrete transforms, compressed sensing, heuristics, branch and bound, conditioning and stability.
When Taught
Winter
Grade Rule
Grade Rule 8: A, B, C, D, E, I (Standard grade rule)
Min
3
Fixed
3
Fixed
3
Fixed
0
Other Prerequisites
concurrent enrollment in Math 323, 346.
Title
Algorithms for approximation and optimization
Learning Outcome
Algorithms for polynomial approximation and interpolation will be presented. Algorithms for optimization will be covered including those for unconstrained optimization, linear optimization, nonlinear constrained optimization, and convex optimization. Dynamic optimization and stochastic problems will also be covered. For a detailed description of desired learning outcomes visit the Math 322 Wiki page.
