This course introduces students to the principals of nonlinear optimization theory and methods. The topics included for this course are 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.
Through this [course_title], you will gain the knowledge of different Algorithm methods. Some of them are the steepest descent, Newton’s method, conditional gradient and subgradient optimization, interior-point methods and penalty and barrier method
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
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Course Credit: MIT
|Duality Theory I||01:25:00|
|Semidefinite Optimization I||01:29:00|
|Submit Your Assignment||00:00:00|
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