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Optimization Theory and Practice
Erik Jonsson School of Engineering and Computer Science
Basics of optimization theory, numerical algorithms, and applications. The course is divided into three main parts: linear programming (simplex method, duality theory), unconstrained methods (optimality conditions, descent algorithms and convergence theorems), and constrained minimization (Lagrange multipliers, Karush-Kuhn-Tucker conditions, active set, penalty and interior point methods). Applications in engineering, operations, finance, statistics, etc. will be emphasized. Students will also use Matlab's optimization toolbox to obtain practical experience with the material. 3 credit hours.
Offering Frequency: Fall
Grades: 22
Median GPA: A
Mean GPA: 3.697
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Optimization Theory and Practice
Erik Jonsson School of Engineering and Computer Science
Basics of optimization theory, numerical algorithms, and applications. The course is divided into three main parts: linear programming (simplex method, duality theory), unconstrained methods (optimality conditions, descent algorithms and convergence theorems), and constrained minimization (Lagrange multipliers, Karush-Kuhn-Tucker conditions, active set, penalty and interior point methods). Applications in engineering, operations, finance, statistics, etc. will be emphasized. Students will also use Matlab's optimization toolbox to obtain practical experience with the material. 3 credit hours.
Offering Frequency: Fall
Grades: 22
Median GPA: A
Mean GPA: 3.697
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Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
SYSM 6305 (Overall) | |||||
A | |||||
SYSM 6305 Justin Ruths | |||||
SYSM 6305 Mark Spong | |||||
A | |||||
Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
SYSM 6305 (Overall) | |||||
A | |||||
SYSM 6305 Justin Ruths | |||||
SYSM 6305 Mark Spong | |||||
A | |||||