IE 411

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 257 or MATH 415.

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.

8/23/2016