Dgp2Dcp-class: Reduce DGP problems to DCP problems.

In CVXR: Disciplined Convex Optimization

Reduce DGP problems to DCP problems.

Description

This reduction takes as input a DGP problem and returns an equivalent DCP problem. Because every (generalized) geometric program is a DGP problem, this reduction can be used to convert geometric programs into convex form.

Usage

## S4 method for signature 'Dgp2Dcp,Problem'
accepts(object, problem)

## S4 method for signature 'Dgp2Dcp,Problem'
perform(object, problem)

## S4 method for signature 'Dgp2Dcp'
canonicalize_expr(object, expr, args)

## S4 method for signature 'Dgp2Dcp,Solution,InverseData'
invert(object, solution, inverse_data)

Arguments

object	A Dgp2Dcp object.
problem	A Problem object.
expr	An Expression object corresponding to the DGP problem.
args	A list of values corresponding to the DGP expression
solution	A Solution object to invert.
inverse_data	A InverseData object containing data necessary for the inversion.

Methods (by generic)

• accepts(object = Dgp2Dcp, problem = Problem): Is the problem DGP?

• perform(object = Dgp2Dcp, problem = Problem): Converts the DGP problem to a DCP problem.

• canonicalize_expr(Dgp2Dcp): Canonicalizes each atom within an Dgp2Dcp expression.

• invert(object = Dgp2Dcp, solution = Solution, inverse_data = InverseData): Returns the solution to the original problem given the inverse_data.

CVXR documentation built on June 27, 2024, 5:11 p.m.