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This course introduces the principal algorithms for linear, network, discrete, nonlinear, dynamic optimization and optimal control.
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English
English [CC]
FREE
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Description
Emphasis is on methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods, branch and bound and cutting plane methods for discrete optimization, optimality conditions for nonlinear optimization, interior point methods for convex optimization, Newton’s method, heuristic methods, and dynamic programming and optimal control methods.
Course content
- Applications of linear optimization Unlimited
- Geometry of linear optimization Unlimited
- Simplex method I Unlimited
- Simplex method II Unlimited
- Duality theory I Unlimited
- Duality theory II Unlimited
- Sensitivity analysis Unlimited
- Robust optimization Unlimited
- Large scale optimization Unlimited
- Network flows I Unlimited
- Network flows II Unlimited
- Applications of discrete optimization Unlimited
- Branch and bound and cutting planes Unlimited
- Lagrangean methods Unlimited
- Heuristics and approximation algorithms Unlimited
- Dynamic programming Unlimited
- Applications of nonlinear optimization Unlimited
- Optimality conditions and gradient methods Unlimited
- Line searches and Newton’s method Unlimited
- Conjugate gradient methods Unlimited
- Affine scaling algorithm Unlimited
- Interior point methods Unlimited
- Semidefinite optimization I Unlimited
- Semidefinite optimization II Unlimited
Instructor
Massachusetts Institute of Technology
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