Constrained Function Optimization

This chapter presents how to combine the equality constraints with the objective function in the optimization process. How to deal with inequality constraints using KKT conditions is presented next. Then, the implementation of quadratic optimization with equality constraints and boundary limits is demonstrated using the \(\mathtt quadprog\) command in Matlab. In the end, the optimization of an arbitrary function subject to nonlinear constraints, linear constraints, and boundary limits is demonstrated using the \(\texttt {fmincon}\) command in Matlab. Function optimization is often subject to constraints in the domain variables. Constraints are of two types: equality constraints and inequality constraints, and the constraints can be linear or nonlinear combinations of domain variables.