Fundamental theory and algorithms of optimization, emphasizing convex optimization. The geometry of convex sets, basic convex analysis, the principle of optimality, duality. Numerical algorithms: steepest descent, Newton’s method, interior point methods, dynamic programming, unimodal search. Applications from engineering and the sciences.
Prerequisites: MATH 120 and 222, or equivalents. May not be taken after AMTH 237.
[Also ECON 536 / AMTH 437 / EENG437/S&DS 430]