This course introduces the principal algorithms for linear, network, nonlinear, dynamic optimization and optimal control. Emphasis is on methodology and the underlying mathematical structures. Topics include such as the simplex method, network flow methods, bound and cutting plane methods for discrete optimization. In addition to that, interior point methods for convex optimization, Newton’s method, dynamic programming and optimal control methods are also discussed in this course.
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 need 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
|Applications of linear optimization||00:14:00|
|Geometry of linear optimization||00:19:00|
|Simplex method I||00:10:00|
|Simplex method II||00:20:00|
|Duality theory I||00:20:00|
|Duality theory II||00:19:00|
|Large scale optimization||00:20:00|
|Network flows I||00:18:00|
|Network flows II||00:18:00|
|Applications of discrete optimization||00:16:00|
|Branch and bound and cutting planes||00:16:00|
|Heuristics and approximation algorithms||00:20:00|
|Applications of nonlinear optimization||00:12:00|
|Optimality conditions and gradient methods||00:17:00|
|Line searches and Newton’s method||00:19:00|
|Conjugate gradient methods||00:19:00|
|Affine scaling algorithm||00:15:00|
|Interior point methods||00:19:00|
|Semidefinite optimization I||00:16:00|
|Semidefinite optimization II||00:20:00|
|Submit Your Assignment||00:00:00|
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