IE 411
IE 411 - Optimization of Large Systems
Fall 2021
| Title | Rubric | Section | CRN | Type | Hours | Times | Days | Location | Instructor |
|---|---|---|---|---|---|---|---|---|---|
| Optimization of Large Systems | IE411 | A | 62888 | LCD | 3 | 1400 - 1520 | T R | 2233 Everitt Laboratory | Xin Chen |
| Optimization of Large Systems | IE411 | AO | 75988 | OLC | 3 | - | Xin Chen | ||
| Optimization of Large Systems | IE411 | B | 62889 | LCD | 4 | 1400 - 1520 | T R | 2233 Everitt Laboratory | Xin Chen |
| Optimization of Large Systems | IE411 | BO | 75989 | OLC | 4 | - | Xin Chen |
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Official Description
Practical methods of optimization of large-scale linear systems including extreme point algorithms, duality theory, parametric linear programming, generalized upper bounding technique, price-directive and resource-directive decomposition techniques, Lagrangian duality, Karmarkar's algorithm, applications in engineering systems, and use of state-of-the-art computer codes. Course Information: 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: IE 310 and MATH 415.
Course Description
This course will cover the modeling, theory and algorithms of linear programming. Specific topics include: various applications using linear programming; geometry of polyhedral sets; the simplex methods; duality theory and applications; sensitivity and parametric analysis; the decomposition principle and column generation; computational complexity; the interior point method; and use of state-of-the-art computer codes. 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: IE 310 and MATH 415.
Last updated
8/23/2016