15.093[J] Optimization Methods
Introduces the principal algorithms for linear, network, discrete, robust, nonlinear, dynamic optimization and optimal control. Emphasizes methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods, branch and bound and cutting plane methods for discrete optimization, optimality conditions for nonlinear optimization, interior point methods for convex optimization, Newton's method, heuristic methods, and dynamic programming and optimal control methods.
This class has 18.06 as a prerequisite.
Lecture occurs 2:30 PM to 4:00 PM on Tuesdays and Thursdays in 32-123.
This class counts for a total of 12 credits. This is a graduate-level class.
You can find more information on MIT OpenCourseWare at the Lecture Notes site.
© Copyright 2015 Yasyf Mohamedali