MATH 482 - Nonlinear Optimization

(3.00)

Introduction to convex analysis. One-dimensional minimization. Unconstrained optimization in algorithms, global convergence and rates of convergence. Quasi-Newton techniques. Convex programming: optimality conditions and duality. Penalty and Barrier methods.

Course ID: 55270
Consent: No Special Consent Required
Components: Lecture
Requirement Group: You must have completed MATH 251 and MATH 301 with a grade of ‘C’ or better before you can enroll in this course. MATH 301 can be taken concurrently.