6.215 Optimization Methods


Class Info

Introduces the principal algorithms for linear, network, discrete, robust, nonlinear, and dynamic optimization. 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. Expectations and evaluation criteria differ for students taking graduate version; consult syllabus or instructor for specific details.

This class has 18.06 as a prerequisite.

6.215 will not be offered this semester. It will be available in the Fall semester, and will be instructed by P. Parrilo and D. Bertsimas.

This class counts for a total of 12 credits.

You can find more information at the http://www.google.com/search?&q=MIT+%2B+6.215&btnG=Google+Search&inurl=https site or on the 6.215 Stellar site.

MIT 6.215 Optimization Methods Related Textbooks

© Copyright 2015