#include <sleipnir/optimization/solver/interior_point.hpp>

Public Attributes
std::function< double(const Eigen::VectorXd &x)>	f

std::function< Eigen::SparseVector< double >(const Eigen::VectorXd &x)>	g

std::function< Eigen::SparseMatrix< double >(const Eigen::VectorXd &x, const Eigen::VectorXd &y, const Eigen::VectorXd &z)>	H

std::function< Eigen::VectorXd(const Eigen::VectorXd &x)>	c_e

std::function< Eigen::SparseMatrix< double >(const Eigen::VectorXd &x)>	A_e

std::function< Eigen::VectorXd(const Eigen::VectorXd &x)>	c_i

std::function< Eigen::SparseMatrix< double >(const Eigen::VectorXd &x)>	A_i

Detailed Description

Matrix callbacks for the interior-point method solver.

Member Data Documentation

◆ A_e

std::function<Eigen::SparseMatrix<double>(const Eigen::VectorXd& x)> slp::InteriorPointMatrixCallbacks::A_e

Equality constraint Jacobian ∂cₑ/∂x getter.

///         [∇ᵀcₑ₁(xₖ)]
/// Aₑ(x) = [∇ᵀcₑ₂(xₖ)]
///         [    ⋮    ]
///         [∇ᵀcₑₘ(xₖ)]
///

<table>
  <tr>
    <th>Variable</th>
    <th>Rows</th>
    <th>Columns</th>
  </tr>
  <tr>
    <td>x</td>
    <td>num_decision_variables</td>
    <td>1</td>
  </tr>
  <tr>
    <td>Aₑ(x)</td>
    <td>num_equality_constraints</td>
    <td>num_decision_variables</td>
  </tr>
</table>

◆ A_i

std::function<Eigen::SparseMatrix<double>(const Eigen::VectorXd& x)> slp::InteriorPointMatrixCallbacks::A_i

Inequality constraint Jacobian ∂cᵢ/∂x getter.

///         [∇ᵀcᵢ₁(xₖ)]
/// Aᵢ(x) = [∇ᵀcᵢ₂(xₖ)]
///         [    ⋮    ]
///         [∇ᵀcᵢₘ(xₖ)]
///

<table>
  <tr>
    <th>Variable</th>
    <th>Rows</th>
    <th>Columns</th>
  </tr>
  <tr>
    <td>x</td>
    <td>num_decision_variables</td>
    <td>1</td>
  </tr>
  <tr>
    <td>Aᵢ(x)</td>
    <td>num_inequality_constraints</td>
    <td>num_decision_variables</td>
  </tr>
</table>

◆ c_e

std::function<Eigen::VectorXd(const Eigen::VectorXd& x)> slp::InteriorPointMatrixCallbacks::c_e

Equality constraint value cₑ(x) getter.

Variable	Rows	Columns
x	num_decision_variables	1
cₑ(x)	num_equality_constraints	1

◆ c_i

std::function<Eigen::VectorXd(const Eigen::VectorXd& x)> slp::InteriorPointMatrixCallbacks::c_i

Inequality constraint value cᵢ(x) getter.

Variable	Rows	Columns
x	num_decision_variables	1
cᵢ(x)	num_inequality_constraints	1

◆ f

std::function<double(const Eigen::VectorXd& x)> slp::InteriorPointMatrixCallbacks::f

Cost function value f(x) getter.

Variable	Rows	Columns
x	num_decision_variables	1
f(x)	1	1

◆ g

std::function<Eigen::SparseVector<double>(const Eigen::VectorXd& x)> slp::InteriorPointMatrixCallbacks::g

Cost function gradient ∇f(x) getter.

Variable	Rows	Columns
x	num_decision_variables	1
∇f(x)	num_decision_variables	1

◆ H

std::function<Eigen::SparseMatrix<double>(const Eigen::VectorXd& x, const Eigen::VectorXd& y, const Eigen::VectorXd& z)> slp::InteriorPointMatrixCallbacks::H

Lagrangian Hessian ∇ₓₓ²L(x, y, z) getter.

L(xₖ, yₖ, zₖ) = f(xₖ) − yₖᵀcₑ(xₖ) − zₖᵀcᵢ(xₖ)

Variable	Rows	Columns
x	num_decision_variables	1
y	num_equality_constraints	1
z	num_inequality_constraints	1
∇ₓₓ²L(x, y, z)	num_decision_variables	num_decision_variables

The documentation for this struct was generated from the following file:

include/sleipnir/optimization/solver/interior_point.hpp

Public Attributes