Optimization Techniques

Catalog description

Algorithms for optimizing real functions of several variables subject to equality and inequality constraints. Convexity properties of functions and sets, linear programming, simplex and interior point methods, integer programming, branch and bound algorithm, transportation problem, necessary and sufficient conditions for nonlinear function optimization, Newton and quasi-Newton methods, Lagrange multiplier conditions, Kuhn-Tucker conditions, dynamic programming. Prerequisite(s): Undergraduate level MTH 2320 Minimum Grade of D and Undergraduate level MTH 2530 Minimum Grade of D Course Level: Undergraduate Schedule Type(s): Lecture Grade Mode: Standard