Read our cookies policy and privacy statement for more information.
×Denver, Colorado•
Every three years. A Ph.D. level course that goes deeper into linear programming, starting from where a graduate-level course (5593) ends. Topics include advanced sensitivity analysis, sparse matrix techniques, and special structures. Additional topics, which vary, include deeper analysis of algorithms, principles of model formulation and solution analysis. Note: This course assumes that students have the equivalent of graduate-level coursework in linear programming (e.g. MATH 5593).
Units: 3.0
Hours: 3 to 3