10. Convex Optimization#
This chapter provides general introduction to convex optimization problems. Convex optimization focuses on a special class of mathematical optimization problems where:
The real valued function being optimized (maximized or minimized) is convex.
The feasible set of values for the function is a closed convex set.
Convex optimization problems are usually further classified into
Quadratic minimization with linear constraints
Quadratic minimization with convex quadratic constraints
Second order cone programming
There are specialized algorithms available for each of these classes.
Some of the applications of convex optimization include:
Worst case risk analysis