SOL Solver Reference: Difference between revisions

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{{Part Of Manual|title=the SOL Manual|link=[[SOL|SOL]]}}
{{Part Of Manual|title=the SOL Manual|link=[[SOL|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.
The SOL solvers are a set of Fortran solvers that were developed by the Stanford Systems Optimization Laboratory (SOL). [[#Table: The SOL optimization solvers in TOMLAB /SOL.]] 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.
Detailed descriptions of the TOMLAB  /SOL solvers are given in the following sections. Also see the M-file help for each solver.
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\mathbb{R}^{m_1}</math> and <math>c_L,c(x),c_U \in \mathbb{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">
====Table: The SOL optimization solvers in TOMLAB /SOL.====
 
{| class="wikitable"
{| class="wikitable"
!Function
!Function
!Description
!Description
|-
|+<caption>The SOL optimization solvers in TOMLAB /SOL.</caption>
|-
|-
|''MINOS 5.5''||Sparse linear and nonlinear programming with linear and nonlinear constraints.
|''MINOS 5.5''||Sparse linear and nonlinear programming with linear and nonlinear constraints.
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|''SQOPT 7.1-1''||Sparse convex quadratic programming.
|''SQOPT 7.1-1''||Sparse convex quadratic programming.
|}
|}
</figtable>


==MINOS==
==MINOS==

Latest revision as of 12:58, 22 January 2012

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). #Table: The SOL optimization solvers in TOMLAB /SOL. 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 .

Table: The SOL optimization solvers in TOMLAB /SOL.

Function Description
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.

MINOS

LP-MINOS

QP-MINOS

LPOPT

QPOPT

LSSOL

NLSSOL

NPSOL

SNOPT

SQOPT