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Last updated:

August 5, 2022

Duration:

Unlimited Duration

FREE

This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration

Description

6.252J is a course in the department’s “Communication, Control, and Signal Processing” concentration.

This course provides a unified analytical and computational approach to nonlinear optimization problems. The topics covered in this course include: unconstrained optimization methods, constrained optimization methods, convex analysis, Lagrangian relaxation, nondifferentiable optimization, and applications in integer programming. There is also a comprehensive treatment of optimality conditions, Lagrange multiplier theory, and duality theory. Throughout the course, applications are drawn from control, communications, power systems, and resource allocation problems.

Course Curriculum

  • Introduction Unlimited
  • Unconstrained Optimization – Optimality Conditions Unlimited
  • Gradient Methods Unlimited
  • Convergence Analysis of Gradient Methods Unlimited
  • Rate of Convergence Unlimited
  • Newton and Gauss – Newton Methods Unlimited
  • Additional Methods Unlimited
  • Optimization Over a Convex Set; Optimality Conditions Unlimited
  • Feasible Direction Methods Unlimited
  • Alternatives to Gradient Projection Unlimited
  • Constrained Optimization; Lagrange Multipliers Unlimited
  • Constrained Optimization; Lagrange Multipliers Unlimited
  • Inequality Constraints Unlimited
  • Introduction to Duality Unlimited
  • Interior Point Methods Unlimited
  • Penalty Methods Unlimited
  • Augmented Lagrangian Methods Unlimited
  • Duality Theory Unlimited
  • Duality Theorems Unlimited
  • Strong Duality Unlimited
  • Additional Dual Methods Unlimited

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Massachusetts Institute of Technology