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9. Nonlinear Convex Optimization (cvxopt.solvers)
In this chapter we consider nonlinear convex
optimization problems of the form
The functions f_k convex and twice differentiabler and the linear inequalities are generalized inequalities with respect to a proper convex cone, defined as a product of a nonnegative orthant, second-order cones, and positive semidefinite cones.
The basic functions are cp() and cpl(), described in sections 9.1 and 9.2. A simpler interface for geometric programming problems is discussed in section 9.3. In section 9.4 we explain how custom solvers can be implemented that exploit structure in specific classes of problems. The last section describes the algorithm parameters that control the solvers.
Subsections