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21690 Fundamentals of Optimization Fall: 12 units An introduction to the theory and algorithms of linear and nonlinear programming with an emphasis on modern computational considerations. The simplex method and its variants, duality theory and sensitivity analysis. Largescale linear programming. Optimality conditions for unconstrained nonlinear optimization. Newton's method, line searches, trust regions and convergence rates. Constrained problems, feasiblepoint methods, penalty and barrier methods, interiorpoint methods. 