This course introduces applications and algorithms for linear, network, integer, and nonlinear optimization. Topics include the primal and dual simplex methods, network flow algorithms, branch and bound, interior point methods, Newton and quasi-Newton methods, and heuristic methods. Students will gain experience in formulating models and implementing algorithms using MATLAB. No previous experience with the software is required.
Course prerequisites: 
Multivariate calculus, linear algebra. Some real analysis would be good but is not required; 625.414 (Linear Optimization) is not required.
Course instructor: 
Castello

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