Optimization@MIT

6.255J -- Optimization Methods
Course Description: Introduces the principal algorithms for linear, network, discrete, nonlinear, dynamic optimization and optimal control. Emphasis on 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 is at the Graduate level
This course is also known as: 15.093J
Instructor: D. Bertsimas, P. Parrilo
Open Courseware Website
Prerequisites: 18.06

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