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Search Results
| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
MECH 6318 (Overall) | |||||
A- | |||||
MECH 6318 Jie Zhang | |||||
A- | |||||
Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
MECH 6318 (Overall) | |||||
A- | |||||
MECH 6318 Jie Zhang | |||||
A- | |||||
Engineering Optimization
MECH 6318
Erik Jonsson School of Engineering and Computer Science
Basics of optimization theory, numerical algorithms, and applications in engineering. The course covers linear programming (simplex method) and nonlinear programming, as well as 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). Non-gradient based optimization methods are briefly introduced. Applications in mechanical engineering design will be emphasized. Students will use Matlab's Optimization Toolbox to obtain practical experience with the material. 3 credit hours.
Offering Frequency: Each year
Grades: 321
Median GPA: A-
Mean GPA: 3.538
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Engineering Optimization
MECH 6318
Erik Jonsson School of Engineering and Computer Science
Basics of optimization theory, numerical algorithms, and applications in engineering. The course covers linear programming (simplex method) and nonlinear programming, as well as 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). Non-gradient based optimization methods are briefly introduced. Applications in mechanical engineering design will be emphasized. Students will use Matlab's Optimization Toolbox to obtain practical experience with the material. 3 credit hours.
Offering Frequency: Each year
Grades: 321
Median GPA: A-
Mean GPA: 3.538
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