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Last updated:

September 20, 2022

Duration:

Unlimited Duration

FREE

This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration

Description

This course introduces students to the fundamentals of nonlinear optimization theory and methods.

Topics include unconstrained and constrained optimization, linear and quadratic programming, Lagrange and conic duality theory, interior-point algorithms and theory, Lagrangian relaxation, generalized programming, and semi-definite programming. Algorithmic methods used in the class include steepest descent, Newton’s method, conditional gradient and subgradient optimization, interior-point methods and penalty and barrier methods.

Course Curriculum

  • Unconstrained Optimization Optimality Conditions Unlimited
  • Newton’s Method Unlimited
  • Quadratic Forms Unlimited
  • Constrained Optimization Optimality Conditions I Unlimited
  • Projection Methods for Equality Constrained Problems Unlimited
  • Projection Methods/Penalty Methods Unlimited
  • Barrier Methods, Conditional Gradient Method Unlimited
  • Interior-Point Methods for Linear Optimization I Unlimited
  • Analysis of Convex Sets Unlimited
  • Duality Theory I Unlimited
  • Duality Theory IV Unlimited
  • Generalized Programming and Subgradient Optimization Unlimited
  • Semidefinite Optimization I Unlimited

About the instructor

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Massachusetts Institute of Technology