SOL Solver Reference: Difference between revisions

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</math>
</math>


where <math>x, x_L, x_U \in \MATHSET{R}^n</math>, <math>f(x) \in \MATHSET{R}</math>, <math>A
where <math>x, x_L, x_U \in \mathbb{R}^n</math>, <math>f(x) \in \mathbb{R}</math>, <math>A
\in \MATHSET{R}^{m_1 \times n}</math>, <math>b_L,b_U \in \MATHSET{R}^{m_1}</math>
\in \mathbb{R}^{m_1 \times n}</math>, <math>b_L,b_U \in \mathbb{R}^{m_1}</math>
and <math>c_L,c(x),c_U \in \MATHSET{R}^{m_2}</math>.
and <math>c_L,c(x),c_U \in \mathbb{R}^{m_2}</math>.




Line 31: Line 31:
</math>
</math>


where <math>c, x, x_L, x_U \in \MATHSET{R}^n</math>, <math>F \in \MATHSET{R}^{n
where <math>c, x, x_L, x_U \in \mathbb{R}^n</math>, <math>F \in \mathbb{R}^{n
\times n}</math>, <math>A \in \MATHSET{R}^{m_1 \times n}</math>, and <math>b_L,b_U \in
\times n}</math>, <math>A \in \mathbb{R}^{m_1 \times n}</math>, and <math>b_L,b_U \in
\MATHSET{R}^{m_1}</math>.
\mathbb{R}^{m_1}</math>.




Line 49: Line 49:
</math>
</math>


where <math>c, x, x_L, x_U \in \MATHSET{R}^n</math>, <math>A \in \MATHSET{R}^{m_1
where <math>c, x, x_L, x_U \in \mathbb{R}^n</math>, <math>A \in \mathbb{R}^{m_1
\times n}</math>, and <math>b_L,b_U \in \MATHSET{R}^{m_1}</math>.
\times n}</math>, and <math>b_L,b_U \in \mathbb{R}^{m_1}</math>.




Line 66: Line 66:
</math>
</math>


where <math>x, x_L, x_U \in \MATHSET{R}^n</math>, <math>d \in \MATHSET{R}^M</math>, <math>C
where <math>x, x_L, x_U \in \mathbb{R}^n</math>, <math>d \in \mathbb{R}^M</math>, <math>C
\in \MATHSET{R}^{M \times n}</math>, <math>A \in \MATHSET{R}^{m_1 \times n}</math>,
\in \mathbb{R}^{M \times n}</math>, <math>A \in \mathbb{R}^{m_1 \times n}</math>,
<math>b_L,b_U \in \MATHSET{R}^{m_1}</math>.
<math>b_L,b_U \in \mathbb{R}^{m_1}</math>.




Line 85: Line 85:
</math>
</math>


where <math>x, x_L, x_U \in \MATHSET{R}^n</math>, <math>r(x) \in \MATHSET{R}^M</math>,
where <math>x, x_L, x_U \in \mathbb{R}^n</math>, <math>r(x) \in \mathbb{R}^M</math>,
<math>A \in \MATHSET{R}^{m_1 \times n}</math>, <math>b_L,b_U \in
<math>A \in \mathbb{R}^{m_1 \times n}</math>, <math>b_L,b_U \in
\MATHSET{R}^{m_1}</math> and <math>c_L,c(x),c_U \in \MATHSET{R}^{m_2}</math>.
\mathbb{R}^{m_1}</math> and <math>c_L,c(x),c_U \in \mathbb{R}^{m_2}</math>.


<figtable id="tab:solSolvers">
<figtable id="tab:solSolvers">

Revision as of 11:14, 9 December 2011

Notice.png

This page is part of the SOL Manual. See SOL.

The SOL solvers are a set of Fortran solvers that were developed by the Stanford Systems Optimization Laboratory (SOL). <xr id="tab:solSolvers" /> lists the solvers included in TOMLAB /SOL. The solvers are called using a set of MEX-file interfaces developed as part of TOMLAB. All functionality of the SOL solvers are available and changeable in the TOMLAB framework in Matlab.

Detailed descriptions of the TOMLAB /SOL solvers are given in the following sections. Also see the M-file help for each solver.

The solvers reference guides for the TOMLAB /SOL solvers are available for download from the TOMLAB home page http://tomopt.com. There is also detailed instruction for using the solvers in SOL Using the SOL Solvers in TOMLAB. Extensive TOMLAB m-file help is also available, for example help snoptTL in Matlab will display the features of the SNOPT solver using the TOMLAB format.

TOMLAB /SOL solves nonlinear optimization problems (con) defined as

where , , , and .


quadratic programming (qp) problems defined as

where , , , and .


linear programming (lp) problems defined as

where , , and .


linear least squares (lls) problems defined as

where , , , , .


and constrained nonlinear least squares problems defined as

where , , , and .

<figtable id="tab:solSolvers">

Function Description
The SOL optimization solvers in TOMLAB /SOL.
MINOS 5.5 Sparse linear and nonlinear programming with linear and nonlinear constraints.
LP-MINOS A special version of the MINOS 5.5 MEX-file interface for sparse linear programming.
QP-MINOS A special version of the MINOS 5.5 MEX-file interface for sparse quadratic programming.
LPOPT 1.0-10 Dense linear programming.
QPOPT 1.0-10 Non-convex quadratic programming with dense constraint matrix and sparse or dense quadratic matrix.
LSSOL 1.05-4 Dense linear and quadratic programs (convex), and constrained linear least squares problems.
NLSSOL 5.0-2 Constrained nonlinear least squares. NLSSOL is based on NPSOL. No reference except for general NPSOL reference.
NPSOL 5.02 Dense linear and nonlinear programming with linear and nonlinear constraints.
SNOPT 7.1-1 Large, sparse linear and nonlinear programming with linear and nonlinear constraints.
SQOPT 7.1-1 Sparse convex quadratic programming.

</figtable>

MINOS

LP-MINOS

QP-MINOS

LPOPT

QPOPT

LSSOL

NLSSOL

NPSOL

SNOPT

SQOPT