Nonlinear Programming
Nonlinear Programming
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.
Duration: Not defined
Level: Graduate
Certification: No
Cost: Free
Language: English
Type: Self-Paced
Please note: these courses are provided by external sources, links are not actively managed or regularly updated, content might be moved or unavailable.
