Nonlinear & Discrete Optimization



IND ENG 160: Nonlinear and Discrete Optimization

Official Course Desctiption

This course introduces unconstrained and constrained optimization with continuous and discrete domains. Convex sets and convex functions; local optimality; KKT conditions; Lagrangian duality; steepest descent and Newton’s method. Modeling with integer variables; branch-and-bound method; cutting planes. Models on production/inventory planning, logistics, portfolio optimization, factor modeling, classification with support vector machines.

For more information about IND ENG 160 visit Berkeley’s Academic Guide.

Class Notes