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This course is an introduction to linear optimization and its extensions emphasizing the underlying mathematical structures, geometrical ideas, algorithms and solutions of practical problems. The topics covered include formulations, the geometry of linear optimization, duality theory, the simplex method, sensitivity analysis, and robust optimization, large scale optimization network flows, solving problems with an exponential number of constraints and the ellipsoid method and interior point methods.


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

Course Curriculum

Module 01
Formulations 00:20:00
Geometry I 00:15:00
Geometry II 00:15:00
Geometry III 00:10:00
Simplex method I 00:10:00
Simplex method II 00:15:00
Simplex method III 00:12:00
Simplex method IV 00:10:00
Duality theory I 00:12:00
Duality theory II 00:12:00
Duality theory III 00:10:00
Sensitivity analysis 00:15:00
Module 02
Robust optimization 00:15:00
Large scale optimization I 00:15:00
Large scale optimization II 00:12:00
Network flows I 00:15:00
Network flows II 00:15:00
The Ellipsoid method 00:15:00
Problems with exponentially many constraints 00:10:00
Interior point methods I 00:12:00
Interior point methods II 00:15:00
Interior point methods III 00:10:00
Semidefinite optimization 00:15:00
Discrete optimization I 00:15:00
Discrete optimization II 00:12:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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