diff options
Diffstat (limited to 'help')
18 files changed, 313 insertions, 53 deletions
diff --git a/help/en_US/lsqlin.xml b/help/en_US/lsqlin.xml index c6ec286..0904933 100644 --- a/help/en_US/lsqlin.xml +++ b/help/en_US/lsqlin.xml @@ -56,7 +56,7 @@ <varlistentry><term>x0 :</term> <listitem><para> a vector of double, contains initial guess of variables.</para></listitem></varlistentry> <varlistentry><term>param :</term> - <listitem><para> a list containing the the parameters to be set.</para></listitem></varlistentry> + <listitem><para> a list containing the parameters to be set.</para></listitem></varlistentry> <varlistentry><term>xopt :</term> <listitem><para> a vector of double, the computed solution of the optimization problem.</para></listitem></varlistentry> <varlistentry><term>resnorm :</term> @@ -64,11 +64,11 @@ <varlistentry><term>residual :</term> <listitem><para> a vector of double, solution residuals returned as the vector d-C*x.</para></listitem></varlistentry> <varlistentry><term>exitflag :</term> - <listitem><para> A flag showing returned exit flag from Ipopt. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro.</para></listitem></varlistentry> + <listitem><para> The exit status. See below for details.</para></listitem></varlistentry> <varlistentry><term>output :</term> - <listitem><para> Structure containing information about the optimization. This version only contains number of iterations.</para></listitem></varlistentry> + <listitem><para> The structure consist of statistics about the optimization. See below for details.</para></listitem></varlistentry> <varlistentry><term>lambda :</term> - <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper bound multiplier and linear equality, inequality constraint multiplier.</para></listitem></varlistentry> + <listitem><para> The structure consist of the Lagrange multipliers at the solution of problem. See below for details.</para></listitem></varlistentry> </variablelist> </refsection> @@ -92,6 +92,39 @@ Search the minimum of a constrained linear least square problem specified by : The routine calls Ipopt for solving the linear least square problem, Ipopt is a library written in C++. </para> <para> +The exitflag allows to know the status of the optimization which is given back by Ipopt. +<itemizedlist> +<listitem>exitflag=0 : Optimal Solution Found </listitem> +<listitem>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</listitem> +<listitem>exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal.</listitem> +<listitem>exitflag=3 : Stop at Tiny Step.</listitem> +<listitem>exitflag=4 : Solved To Acceptable Level.</listitem> +<listitem>exitflag=5 : Converged to a point of local infeasibility.</listitem> +</itemizedlist> + </para> + <para> +For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/ + </para> + <para> +The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>output.iterations: The number of iterations performed during the search</listitem> +<listitem>output.constrviolation: The max-norm of the constraint violation.</listitem> +</itemizedlist> + </para> + <para> +The lambda data structure contains the Lagrange multipliers at the end +of optimization. In the current version the values are returned only when the the solution is optimal. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>lambda.lower: The Lagrange multipliers for the lower bound constraints.</listitem> +<listitem>lambda.upper: The Lagrange multipliers for the upper bound constraints.</listitem> +<listitem>lambda.eqlin: The Lagrange multipliers for the linear equality constraints.</listitem> +<listitem>lambda.ineqlin: The Lagrange multipliers for the linear inequality constraints.</listitem> +</itemizedlist> + </para> + <para> </para> </refsection> diff --git a/help/en_US/lsqnonneg.xml b/help/en_US/lsqnonneg.xml index 5d78bbd..201e878 100644 --- a/help/en_US/lsqnonneg.xml +++ b/help/en_US/lsqnonneg.xml @@ -45,11 +45,11 @@ <varlistentry><term>residual :</term> <listitem><para> a vector of double, solution residuals returned as the vector d-C*x.</para></listitem></varlistentry> <varlistentry><term>exitflag :</term> - <listitem><para> A flag showing returned exit flag from Ipopt. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro.</para></listitem></varlistentry> + <listitem><para> The exit status. See below for details.</para></listitem></varlistentry> <varlistentry><term>output :</term> - <listitem><para> Structure containing information about the optimization. This version only contains number of iterations.</para></listitem></varlistentry> + <listitem><para> The structure consist of statistics about the optimization. See below for details.</para></listitem></varlistentry> <varlistentry><term>lambda :</term> - <listitem><para> Structure containing the Lagrange multipliers at the solution xopt. It contains lower, upper bound multiplier and linear equality, inequality constraint multiplier.</para></listitem></varlistentry> + <listitem><para> The structure consist of the Lagrange multipliers at the solution of problem. See below for details.</para></listitem></varlistentry> </variablelist> </refsection> @@ -71,6 +71,37 @@ Solves nonnegative least-squares curve fitting problems specified by : The routine calls Ipopt for solving the nonnegative least-squares curve fitting problems, Ipopt is a library written in C++. </para> <para> +The exitflag allows to know the status of the optimization which is given back by Ipopt. +<itemizedlist> +<listitem>exitflag=0 : Optimal Solution Found </listitem> +<listitem>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</listitem> +<listitem>exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal.</listitem> +<listitem>exitflag=3 : Stop at Tiny Step.</listitem> +<listitem>exitflag=4 : Solved To Acceptable Level.</listitem> +<listitem>exitflag=5 : Converged to a point of local infeasibility.</listitem> +</itemizedlist> + </para> + <para> +For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/ + </para> + <para> +The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>output.iterations: The number of iterations performed during the search</listitem> +<listitem>output.constrviolation: The max-norm of the constraint violation.</listitem> +</itemizedlist> + </para> + <para> +The lambda data structure contains the Lagrange multipliers at the end +of optimization. In the current version the values are returned only when the the solution is optimal. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>lambda.lower: The Lagrange multipliers for the lower bound constraints.</listitem> +<listitem>lambda.upper: The Lagrange multipliers for the upper bound constraints.</listitem> +</itemizedlist> + </para> + <para> </para> </refsection> diff --git a/help/en_US/qpipopt.xml b/help/en_US/qpipopt.xml index 3ba2107..170b457 100644 --- a/help/en_US/qpipopt.xml +++ b/help/en_US/qpipopt.xml @@ -48,7 +48,7 @@ <varlistentry><term>ub :</term> <listitem><para> a vector of double, contains upper bounds of the variables.</para></listitem></varlistentry> <varlistentry><term>A :</term> - <listitem><para> a matrix of double, contains matrix representing the constraint matrix</para></listitem></varlistentry> + <listitem><para> a matrix of double, contains the constraint matrix</para></listitem></varlistentry> <varlistentry><term>conLB :</term> <listitem><para> a vector of double, contains lower bounds of the constraints.</para></listitem></varlistentry> <varlistentry><term>conUB :</term> @@ -56,17 +56,17 @@ <varlistentry><term>x0 :</term> <listitem><para> a vector of double, contains initial guess of variables.</para></listitem></varlistentry> <varlistentry><term>param :</term> - <listitem><para> a list containing the the parameters to be set.</para></listitem></varlistentry> + <listitem><para> a list containing the parameters to be set.</para></listitem></varlistentry> <varlistentry><term>xopt :</term> <listitem><para> a vector of double, the computed solution of the optimization problem.</para></listitem></varlistentry> <varlistentry><term>fopt :</term> - <listitem><para> a double, the function value at x.</para></listitem></varlistentry> + <listitem><para> a double, the value of the function at x.</para></listitem></varlistentry> <varlistentry><term>exitflag :</term> - <listitem><para> A flag showing returned exit flag from Ipopt. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro.</para></listitem></varlistentry> + <listitem><para> The exit status. See below for details.</para></listitem></varlistentry> <varlistentry><term>output :</term> - <listitem><para> Structure containing information about the optimization. This version only contains number of iterations</para></listitem></varlistentry> + <listitem><para> The structure consist of statistics about the optimization. See below for details.</para></listitem></varlistentry> <varlistentry><term>lambda :</term> - <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper bound multiplier and linear equality, inequality constraint multiplier.</para></listitem></varlistentry> + <listitem><para> The structure consist of the Lagrange multipliers at the solution of problem. See below for details.</para></listitem></varlistentry> </variablelist> </refsection> @@ -89,6 +89,39 @@ Search the minimum of a constrained linear quadratic optimization problem specif The routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++. </para> <para> +The exitflag allows to know the status of the optimization which is given back by Ipopt. +<itemizedlist> +<listitem>exitflag=0 : Optimal Solution Found </listitem> +<listitem>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</listitem> +<listitem>exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal.</listitem> +<listitem>exitflag=3 : Stop at Tiny Step.</listitem> +<listitem>exitflag=4 : Solved To Acceptable Level.</listitem> +<listitem>exitflag=5 : Converged to a point of local infeasibility.</listitem> +</itemizedlist> + </para> + <para> +For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/ + </para> + <para> +The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>output.iterations: The number of iterations performed during the search</listitem> +<listitem>output.constrviolation: The max-norm of the constraint violation.</listitem> +</itemizedlist> + </para> + <para> +The lambda data structure contains the Lagrange multipliers at the end +of optimization. In the current version the values are returned only when the the solution is optimal. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>lambda.lower: The Lagrange multipliers for the lower bound constraints.</listitem> +<listitem>lambda.upper: The Lagrange multipliers for the upper bound constraints.</listitem> +<listitem>lambda.eqlin: The Lagrange multipliers for the linear equality constraints.</listitem> +<listitem>lambda.ineqlin: The Lagrange multipliers for the linear inequality constraints.</listitem> +</itemizedlist> + </para> + <para> </para> </refsection> diff --git a/help/en_US/qpipoptmat.xml b/help/en_US/qpipoptmat.xml index 1334603..82249a7 100644 --- a/help/en_US/qpipoptmat.xml +++ b/help/en_US/qpipoptmat.xml @@ -57,19 +57,19 @@ <varlistentry><term>x0 :</term> <listitem><para> a vector of double, contains initial guess of variables.</para></listitem></varlistentry> <varlistentry><term>param :</term> - <listitem><para> a list containing the the parameters to be set.</para></listitem></varlistentry> + <listitem><para> a list containing the parameters to be set.</para></listitem></varlistentry> <varlistentry><term>xopt :</term> <listitem><para> a vector of double, the computed solution of the optimization problem.</para></listitem></varlistentry> <varlistentry><term>fopt :</term> - <listitem><para> a double, the function value at x.</para></listitem></varlistentry> + <listitem><para> a double, the value of the function at x.</para></listitem></varlistentry> <varlistentry><term>residual :</term> <listitem><para> a vector of double, solution residuals returned as the vector d-C*x.</para></listitem></varlistentry> <varlistentry><term>exitflag :</term> - <listitem><para> A flag showing returned exit flag from Ipopt. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro.</para></listitem></varlistentry> + <listitem><para> The exit status. See below for details.</para></listitem></varlistentry> <varlistentry><term>output :</term> - <listitem><para> Structure containing information about the optimization. This version only contains number of iterations.</para></listitem></varlistentry> + <listitem><para> The structure consist of statistics about the optimization. See below for details.</para></listitem></varlistentry> <varlistentry><term>lambda :</term> - <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper bound multiplier and linear equality, inequality constraint multiplier.</para></listitem></varlistentry> + <listitem><para> The structure consist of the Lagrange multipliers at the solution of problem. See below for details.</para></listitem></varlistentry> </variablelist> </refsection> @@ -93,6 +93,39 @@ Search the minimum of a constrained linear quadratic optimization problem specif The routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++. </para> <para> +The exitflag allows to know the status of the optimization which is given back by Ipopt. +<itemizedlist> +<listitem>exitflag=0 : Optimal Solution Found </listitem> +<listitem>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</listitem> +<listitem>exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal.</listitem> +<listitem>exitflag=3 : Stop at Tiny Step.</listitem> +<listitem>exitflag=4 : Solved To Acceptable Level.</listitem> +<listitem>exitflag=5 : Converged to a point of local infeasibility.</listitem> +</itemizedlist> + </para> + <para> +For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/ + </para> + <para> +The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>output.iterations: The number of iterations performed during the search</listitem> +<listitem>output.constrviolation: The max-norm of the constraint violation.</listitem> +</itemizedlist> + </para> + <para> +The lambda data structure contains the Lagrange multipliers at the end +of optimization. In the current version the values are returned only when the the solution is optimal. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>lambda.lower: The Lagrange multipliers for the lower bound constraints.</listitem> +<listitem>lambda.upper: The Lagrange multipliers for the upper bound constraints.</listitem> +<listitem>lambda.eqlin: The Lagrange multipliers for the linear equality constraints.</listitem> +<listitem>lambda.ineqlin: The Lagrange multipliers for the linear inequality constraints.</listitem> +</itemizedlist> + </para> + <para> </para> </refsection> diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS Binary files differindex d3146bf..8323669 100644 --- a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB Binary files differindex f0a1fcb..ba30e61 100644 --- a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS b/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS Binary files differindex 8a63187..6e8476f 100644 --- a/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS b/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS Binary files differindex 423d132..9cd3f49 100644 --- a/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA b/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA index 6df2edb..f4e9ef7 100644 --- a/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA @@ -1,2 +1,2 @@ JavaSearch 1.0 -TMAP bs=2048 rt=1 fl=-1 id1=1249 id2=1 +TMAP bs=2048 rt=1 fl=-1 id1=1280 id2=1 diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP b/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP Binary files differindex 6104335..12891d8 100644 --- a/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP diff --git a/help/en_US/scilab_en_US_help/lsqlin.html b/help/en_US/scilab_en_US_help/lsqlin.html index e9253c5..7dbb227 100644 --- a/help/en_US/scilab_en_US_help/lsqlin.html +++ b/help/en_US/scilab_en_US_help/lsqlin.html @@ -64,7 +64,7 @@ <dt><span class="term">x0 :</span> <dd><p class="para">a vector of double, contains initial guess of variables.</p></dd></dt> <dt><span class="term">param :</span> - <dd><p class="para">a list containing the the parameters to be set.</p></dd></dt> + <dd><p class="para">a list containing the parameters to be set.</p></dd></dt> <dt><span class="term">xopt :</span> <dd><p class="para">a vector of double, the computed solution of the optimization problem.</p></dd></dt> <dt><span class="term">resnorm :</span> @@ -72,16 +72,35 @@ <dt><span class="term">residual :</span> <dd><p class="para">a vector of double, solution residuals returned as the vector d-C*x.</p></dd></dt> <dt><span class="term">exitflag :</span> - <dd><p class="para">A flag showing returned exit flag from Ipopt. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro.</p></dd></dt> + <dd><p class="para">The exit status. See below for details.</p></dd></dt> <dt><span class="term">output :</span> - <dd><p class="para">Structure containing information about the optimization. This version only contains number of iterations.</p></dd></dt> + <dd><p class="para">The structure consist of statistics about the optimization. See below for details.</p></dd></dt> <dt><span class="term">lambda :</span> - <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper bound multiplier and linear equality, inequality constraint multiplier.</p></dd></dt></dl></div> + <dd><p class="para">The structure consist of the Lagrange multipliers at the solution of problem. See below for details.</p></dd></dt></dl></div> <div class="refsection"><h3 class="title">Description</h3> <p class="para">Search the minimum of a constrained linear least square problem specified by :</p> <p class="para"><span><img src='./_LaTeX_lsqlin.xml_1.png' style='position:relative;top:41px;width:230px;height:90px'/></span></p> <p class="para">The routine calls Ipopt for solving the linear least square problem, Ipopt is a library written in C++.</p> + <p class="para">The exitflag allows to know the status of the optimization which is given back by Ipopt. +<ul class="itemizedlist"><li>exitflag=0 : Optimal Solution Found</li> +<li>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</li> +<li>exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal.</li> +<li>exitflag=3 : Stop at Tiny Step.</li> +<li>exitflag=4 : Solved To Acceptable Level.</li> +<li>exitflag=5 : Converged to a point of local infeasibility.</li></ul></p> + <p class="para">For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/</p> + <p class="para">The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>output.iterations: The number of iterations performed during the search</li> +<li>output.constrviolation: The max-norm of the constraint violation.</li></ul></p> + <p class="para">The lambda data structure contains the Lagrange multipliers at the end +of optimization. In the current version the values are returned only when the the solution is optimal. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>lambda.lower: The Lagrange multipliers for the lower bound constraints.</li> +<li>lambda.upper: The Lagrange multipliers for the upper bound constraints.</li> +<li>lambda.eqlin: The Lagrange multipliers for the linear equality constraints.</li> +<li>lambda.ineqlin: The Lagrange multipliers for the linear inequality constraints.</li></ul></p> <p class="para"></p></div> <div class="refsection"><h3 class="title">Examples</h3> diff --git a/help/en_US/scilab_en_US_help/lsqnonneg.html b/help/en_US/scilab_en_US_help/lsqnonneg.html index 7211c40..a8e6801 100644 --- a/help/en_US/scilab_en_US_help/lsqnonneg.html +++ b/help/en_US/scilab_en_US_help/lsqnonneg.html @@ -53,16 +53,33 @@ <dt><span class="term">residual :</span> <dd><p class="para">a vector of double, solution residuals returned as the vector d-C*x.</p></dd></dt> <dt><span class="term">exitflag :</span> - <dd><p class="para">A flag showing returned exit flag from Ipopt. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro.</p></dd></dt> + <dd><p class="para">The exit status. See below for details.</p></dd></dt> <dt><span class="term">output :</span> - <dd><p class="para">Structure containing information about the optimization. This version only contains number of iterations.</p></dd></dt> + <dd><p class="para">The structure consist of statistics about the optimization. See below for details.</p></dd></dt> <dt><span class="term">lambda :</span> - <dd><p class="para">Structure containing the Lagrange multipliers at the solution xopt. It contains lower, upper bound multiplier and linear equality, inequality constraint multiplier.</p></dd></dt></dl></div> + <dd><p class="para">The structure consist of the Lagrange multipliers at the solution of problem. See below for details.</p></dd></dt></dl></div> <div class="refsection"><h3 class="title">Description</h3> <p class="para">Solves nonnegative least-squares curve fitting problems specified by :</p> <p class="para"><span><img src='./_LaTeX_lsqnonneg.xml_1.png' style='position:relative;top:19px;width:193px;height:46px'/></span></p> <p class="para">The routine calls Ipopt for solving the nonnegative least-squares curve fitting problems, Ipopt is a library written in C++.</p> + <p class="para">The exitflag allows to know the status of the optimization which is given back by Ipopt. +<ul class="itemizedlist"><li>exitflag=0 : Optimal Solution Found</li> +<li>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</li> +<li>exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal.</li> +<li>exitflag=3 : Stop at Tiny Step.</li> +<li>exitflag=4 : Solved To Acceptable Level.</li> +<li>exitflag=5 : Converged to a point of local infeasibility.</li></ul></p> + <p class="para">For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/</p> + <p class="para">The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>output.iterations: The number of iterations performed during the search</li> +<li>output.constrviolation: The max-norm of the constraint violation.</li></ul></p> + <p class="para">The lambda data structure contains the Lagrange multipliers at the end +of optimization. In the current version the values are returned only when the the solution is optimal. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>lambda.lower: The Lagrange multipliers for the lower bound constraints.</li> +<li>lambda.upper: The Lagrange multipliers for the upper bound constraints.</li></ul></p> <p class="para"></p></div> <div class="refsection"><h3 class="title">Examples</h3> diff --git a/help/en_US/scilab_en_US_help/qpipopt.html b/help/en_US/scilab_en_US_help/qpipopt.html index 31f389f..fc08a81 100644 --- a/help/en_US/scilab_en_US_help/qpipopt.html +++ b/help/en_US/scilab_en_US_help/qpipopt.html @@ -56,7 +56,7 @@ <dt><span class="term">ub :</span> <dd><p class="para">a vector of double, contains upper bounds of the variables.</p></dd></dt> <dt><span class="term">A :</span> - <dd><p class="para">a matrix of double, contains matrix representing the constraint matrix</p></dd></dt> + <dd><p class="para">a matrix of double, contains the constraint matrix</p></dd></dt> <dt><span class="term">conLB :</span> <dd><p class="para">a vector of double, contains lower bounds of the constraints.</p></dd></dt> <dt><span class="term">conUB :</span> @@ -64,22 +64,41 @@ <dt><span class="term">x0 :</span> <dd><p class="para">a vector of double, contains initial guess of variables.</p></dd></dt> <dt><span class="term">param :</span> - <dd><p class="para">a list containing the the parameters to be set.</p></dd></dt> + <dd><p class="para">a list containing the parameters to be set.</p></dd></dt> <dt><span class="term">xopt :</span> <dd><p class="para">a vector of double, the computed solution of the optimization problem.</p></dd></dt> <dt><span class="term">fopt :</span> - <dd><p class="para">a double, the function value at x.</p></dd></dt> + <dd><p class="para">a double, the value of the function at x.</p></dd></dt> <dt><span class="term">exitflag :</span> - <dd><p class="para">A flag showing returned exit flag from Ipopt. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro.</p></dd></dt> + <dd><p class="para">The exit status. See below for details.</p></dd></dt> <dt><span class="term">output :</span> - <dd><p class="para">Structure containing information about the optimization. This version only contains number of iterations</p></dd></dt> + <dd><p class="para">The structure consist of statistics about the optimization. See below for details.</p></dd></dt> <dt><span class="term">lambda :</span> - <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper bound multiplier and linear equality, inequality constraint multiplier.</p></dd></dt></dl></div> + <dd><p class="para">The structure consist of the Lagrange multipliers at the solution of problem. See below for details.</p></dd></dt></dl></div> <div class="refsection"><h3 class="title">Description</h3> <p class="para">Search the minimum of a constrained linear quadratic optimization problem specified by :</p> <p class="para"><span><img src='./_LaTeX_qpipopt.xml_1.png' style='position:relative;top:31px;width:292px;height:70px'/></span></p> <p class="para">The routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++.</p> + <p class="para">The exitflag allows to know the status of the optimization which is given back by Ipopt. +<ul class="itemizedlist"><li>exitflag=0 : Optimal Solution Found</li> +<li>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</li> +<li>exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal.</li> +<li>exitflag=3 : Stop at Tiny Step.</li> +<li>exitflag=4 : Solved To Acceptable Level.</li> +<li>exitflag=5 : Converged to a point of local infeasibility.</li></ul></p> + <p class="para">For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/</p> + <p class="para">The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>output.iterations: The number of iterations performed during the search</li> +<li>output.constrviolation: The max-norm of the constraint violation.</li></ul></p> + <p class="para">The lambda data structure contains the Lagrange multipliers at the end +of optimization. In the current version the values are returned only when the the solution is optimal. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>lambda.lower: The Lagrange multipliers for the lower bound constraints.</li> +<li>lambda.upper: The Lagrange multipliers for the upper bound constraints.</li> +<li>lambda.eqlin: The Lagrange multipliers for the linear equality constraints.</li> +<li>lambda.ineqlin: The Lagrange multipliers for the linear inequality constraints.</li></ul></p> <p class="para"></p></div> <div class="refsection"><h3 class="title">Examples</h3> diff --git a/help/en_US/scilab_en_US_help/qpipoptmat.html b/help/en_US/scilab_en_US_help/qpipoptmat.html index 6c195ea..4a89648 100644 --- a/help/en_US/scilab_en_US_help/qpipoptmat.html +++ b/help/en_US/scilab_en_US_help/qpipoptmat.html @@ -65,24 +65,43 @@ <dt><span class="term">x0 :</span> <dd><p class="para">a vector of double, contains initial guess of variables.</p></dd></dt> <dt><span class="term">param :</span> - <dd><p class="para">a list containing the the parameters to be set.</p></dd></dt> + <dd><p class="para">a list containing the parameters to be set.</p></dd></dt> <dt><span class="term">xopt :</span> <dd><p class="para">a vector of double, the computed solution of the optimization problem.</p></dd></dt> <dt><span class="term">fopt :</span> - <dd><p class="para">a double, the function value at x.</p></dd></dt> + <dd><p class="para">a double, the value of the function at x.</p></dd></dt> <dt><span class="term">residual :</span> <dd><p class="para">a vector of double, solution residuals returned as the vector d-C*x.</p></dd></dt> <dt><span class="term">exitflag :</span> - <dd><p class="para">A flag showing returned exit flag from Ipopt. It could be 0, 1 or 2 etc. i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded. Other flags one can see in the lsqlin macro.</p></dd></dt> + <dd><p class="para">The exit status. See below for details.</p></dd></dt> <dt><span class="term">output :</span> - <dd><p class="para">Structure containing information about the optimization. This version only contains number of iterations.</p></dd></dt> + <dd><p class="para">The structure consist of statistics about the optimization. See below for details.</p></dd></dt> <dt><span class="term">lambda :</span> - <dd><p class="para">Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper bound multiplier and linear equality, inequality constraint multiplier.</p></dd></dt></dl></div> + <dd><p class="para">The structure consist of the Lagrange multipliers at the solution of problem. See below for details.</p></dd></dt></dl></div> <div class="refsection"><h3 class="title">Description</h3> <p class="para">Search the minimum of a constrained linear quadratic optimization problem specified by :</p> <p class="para"><span><img src='./_LaTeX_qpipoptmat.xml_1.png' style='position:relative;top:41px;width:277px;height:90px'/></span></p> <p class="para">The routine calls Ipopt for solving the quadratic problem, Ipopt is a library written in C++.</p> + <p class="para">The exitflag allows to know the status of the optimization which is given back by Ipopt. +<ul class="itemizedlist"><li>exitflag=0 : Optimal Solution Found</li> +<li>exitflag=1 : Maximum Number of Iterations Exceeded. Output may not be optimal.</li> +<li>exitflag=2 : Maximum CPU Time exceeded. Output may not be optimal.</li> +<li>exitflag=3 : Stop at Tiny Step.</li> +<li>exitflag=4 : Solved To Acceptable Level.</li> +<li>exitflag=5 : Converged to a point of local infeasibility.</li></ul></p> + <p class="para">For more details on exitflag see the ipopt documentation, go to http://www.coin-or.org/Ipopt/documentation/</p> + <p class="para">The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>output.iterations: The number of iterations performed during the search</li> +<li>output.constrviolation: The max-norm of the constraint violation.</li></ul></p> + <p class="para">The lambda data structure contains the Lagrange multipliers at the end +of optimization. In the current version the values are returned only when the the solution is optimal. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>lambda.lower: The Lagrange multipliers for the lower bound constraints.</li> +<li>lambda.upper: The Lagrange multipliers for the upper bound constraints.</li> +<li>lambda.eqlin: The Lagrange multipliers for the linear equality constraints.</li> +<li>lambda.ineqlin: The Lagrange multipliers for the linear inequality constraints.</li></ul></p> <p class="para"></p></div> <div class="refsection"><h3 class="title">Examples</h3> diff --git a/help/en_US/scilab_en_US_help/symphony.html b/help/en_US/scilab_en_US_help/symphony.html index e374a30..d5b21cd 100644 --- a/help/en_US/scilab_en_US_help/symphony.html +++ b/help/en_US/scilab_en_US_help/symphony.html @@ -64,20 +64,29 @@ <dt><span class="term">objSense :</span> <dd><p class="para">The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here.</p></dd></dt> <dt><span class="term">options :</span> - <dd><p class="para">a list containing the the parameters to be set.</p></dd></dt> + <dd><p class="para">a list containing the parameters to be set.</p></dd></dt> <dt><span class="term">xopt :</span> <dd><p class="para">a vector of double, the computed solution of the optimization problem.</p></dd></dt> <dt><span class="term">fopt :</span> - <dd><p class="para">a double, the function value at x.</p></dd></dt> + <dd><p class="para">a double, the value of the function at x.</p></dd></dt> <dt><span class="term">status :</span> - <dd><p class="para">status flag returned from symphony. 227 is optimal, 228 is Time limit exceeded, 230 is iteration limit exceeded.</p></dd></dt> + <dd><p class="para">status flag returned from symphony.See below for details.</p></dd></dt> <dt><span class="term">output :</span> - <dd><p class="para">The output data structure contains detailed information about the optimization process. This version only contains number of iterations</p></dd></dt></dl></div> + <dd><p class="para">The output data structure contains detailed information about the optimization process. See below for details.</p></dd></dt></dl></div> <div class="refsection"><h3 class="title">Description</h3> <p class="para">Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :</p> <p class="para"><span><img src='./_LaTeX_symphony.xml_1.png' style='position:relative;top:41px;width:292px;height:90px'/></span></p> <p class="para">The routine calls SYMPHONY written in C by gateway files for the actual computation.</p> + <p class="para">The status allows to know the status of the optimization which is given back by Ipopt. +<ul class="itemizedlist"><li>status=227 : Optimal Solution Found</li> +<li>status=228 : Maximum CPU Time exceeded.</li> +<li>status=229 : Maximum Number of Node Limit Exceeded.</li> +<li>status=230 : Maximum Number of Iterations Limit Exceeded.</li></ul></p> + <p class="para">For more details on status see the symphony documentation, go to http://www.coin-or.org/SYMPHONY/man-5.6/</p> + <p class="para">The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>output.iterations: The number of iterations performed during the search</li></ul></p> <p class="para"></p></div> <div class="refsection"><h3 class="title">Examples</h3> diff --git a/help/en_US/scilab_en_US_help/symphonymat.html b/help/en_US/scilab_en_US_help/symphonymat.html index 203f2d4..db8ffee 100644 --- a/help/en_US/scilab_en_US_help/symphonymat.html +++ b/help/en_US/scilab_en_US_help/symphonymat.html @@ -61,20 +61,29 @@ <dt><span class="term">ub :</span> <dd><p class="para">Upper bounds, specified as a vector or array of double. ub represents the upper bounds elementwise in lb ≤ x ≤ ub.</p></dd></dt> <dt><span class="term">options :</span> - <dd><p class="para">a list containing the the parameters to be set.</p></dd></dt> + <dd><p class="para">a list containing the parameters to be set.</p></dd></dt> <dt><span class="term">xopt :</span> <dd><p class="para">a vector of double, the computed solution of the optimization problem.</p></dd></dt> <dt><span class="term">fopt :</span> - <dd><p class="para">a double, the function value at x</p></dd></dt> + <dd><p class="para">a double, the value of the function at x.</p></dd></dt> <dt><span class="term">status :</span> - <dd><p class="para">status flag returned from symphony. 227 is optimal, 228 is Time limit exceeded, 230 is iteration limit exceeded.</p></dd></dt> + <dd><p class="para">status flag returned from symphony. See below for details.</p></dd></dt> <dt><span class="term">output :</span> - <dd><p class="para">The output data structure contains detailed information about the optimization process. This version only contains number of iterations.</p></dd></dt></dl></div> + <dd><p class="para">The output data structure contains detailed information about the optimization process. See below for details.</p></dd></dt></dl></div> <div class="refsection"><h3 class="title">Description</h3> <p class="para">Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by :</p> <p class="para"><span><img src='./_LaTeX_symphonymat.xml_1.png' style='position:relative;top:51px;width:212px;height:110px'/></span></p> <p class="para">The routine calls SYMPHONY written in C by gateway files for the actual computation.</p> + <p class="para">The status allows to know the status of the optimization which is given back by Ipopt. +<ul class="itemizedlist"><li>status=227 : Optimal Solution Found</li> +<li>status=228 : Maximum CPU Time exceeded.</li> +<li>status=229 : Maximum Number of Node Limit Exceeded.</li> +<li>status=230 : Maximum Number of Iterations Limit Exceeded.</li></ul></p> + <p class="para">For more details on status see the symphony documentation, go to http://www.coin-or.org/SYMPHONY/man-5.6/</p> + <p class="para">The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<ul class="itemizedlist"><li>output.iterations: The number of iterations performed during the search</li></ul></p> <p class="para"></p></div> <div class="refsection"><h3 class="title">Examples</h3> diff --git a/help/en_US/symphony.xml b/help/en_US/symphony.xml index da156ce..68f1742 100644 --- a/help/en_US/symphony.xml +++ b/help/en_US/symphony.xml @@ -56,15 +56,15 @@ <varlistentry><term>objSense :</term> <listitem><para> The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here.</para></listitem></varlistentry> <varlistentry><term>options :</term> - <listitem><para> a list containing the the parameters to be set.</para></listitem></varlistentry> + <listitem><para> a list containing the parameters to be set.</para></listitem></varlistentry> <varlistentry><term>xopt :</term> <listitem><para> a vector of double, the computed solution of the optimization problem.</para></listitem></varlistentry> <varlistentry><term>fopt :</term> - <listitem><para> a double, the function value at x.</para></listitem></varlistentry> + <listitem><para> a double, the value of the function at x.</para></listitem></varlistentry> <varlistentry><term>status :</term> - <listitem><para> status flag returned from symphony. 227 is optimal, 228 is Time limit exceeded, 230 is iteration limit exceeded.</para></listitem></varlistentry> + <listitem><para> status flag returned from symphony.See below for details.</para></listitem></varlistentry> <varlistentry><term>output :</term> - <listitem><para> The output data structure contains detailed information about the optimization process. This version only contains number of iterations</para></listitem></varlistentry> + <listitem><para> The output data structure contains detailed information about the optimization process. See below for details.</para></listitem></varlistentry> </variablelist> </refsection> @@ -88,6 +88,25 @@ Search the minimum or maximum of a constrained mixed integer linear programming The routine calls SYMPHONY written in C by gateway files for the actual computation. </para> <para> +The status allows to know the status of the optimization which is given back by Ipopt. +<itemizedlist> +<listitem>status=227 : Optimal Solution Found </listitem> +<listitem>status=228 : Maximum CPU Time exceeded.</listitem> +<listitem>status=229 : Maximum Number of Node Limit Exceeded.</listitem> +<listitem>status=230 : Maximum Number of Iterations Limit Exceeded.</listitem> +</itemizedlist> + </para> + <para> +For more details on status see the symphony documentation, go to http://www.coin-or.org/SYMPHONY/man-5.6/ + </para> + <para> +The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>output.iterations: The number of iterations performed during the search</listitem> +</itemizedlist> + </para> + <para> </para> </refsection> diff --git a/help/en_US/symphonymat.xml b/help/en_US/symphonymat.xml index 68ec072..33ed973 100644 --- a/help/en_US/symphonymat.xml +++ b/help/en_US/symphonymat.xml @@ -53,15 +53,15 @@ <varlistentry><term>ub :</term> <listitem><para> Upper bounds, specified as a vector or array of double. ub represents the upper bounds elementwise in lb ≤ x ≤ ub.</para></listitem></varlistentry> <varlistentry><term>options :</term> - <listitem><para> a list containing the the parameters to be set.</para></listitem></varlistentry> + <listitem><para> a list containing the parameters to be set.</para></listitem></varlistentry> <varlistentry><term>xopt :</term> <listitem><para> a vector of double, the computed solution of the optimization problem.</para></listitem></varlistentry> <varlistentry><term>fopt :</term> - <listitem><para> a double, the function value at x</para></listitem></varlistentry> + <listitem><para> a double, the value of the function at x.</para></listitem></varlistentry> <varlistentry><term>status :</term> - <listitem><para> status flag returned from symphony. 227 is optimal, 228 is Time limit exceeded, 230 is iteration limit exceeded.</para></listitem></varlistentry> + <listitem><para> status flag returned from symphony. See below for details.</para></listitem></varlistentry> <varlistentry><term>output :</term> - <listitem><para> The output data structure contains detailed information about the optimization process. This version only contains number of iterations.</para></listitem></varlistentry> + <listitem><para> The output data structure contains detailed information about the optimization process. See below for details.</para></listitem></varlistentry> </variablelist> </refsection> @@ -86,6 +86,25 @@ Search the minimum or maximum of a constrained mixed integer linear programming The routine calls SYMPHONY written in C by gateway files for the actual computation. </para> <para> +The status allows to know the status of the optimization which is given back by Ipopt. +<itemizedlist> +<listitem>status=227 : Optimal Solution Found </listitem> +<listitem>status=228 : Maximum CPU Time exceeded.</listitem> +<listitem>status=229 : Maximum Number of Node Limit Exceeded.</listitem> +<listitem>status=230 : Maximum Number of Iterations Limit Exceeded.</listitem> +</itemizedlist> + </para> + <para> +For more details on status see the symphony documentation, go to http://www.coin-or.org/SYMPHONY/man-5.6/ + </para> + <para> +The output data structure contains detailed informations about the optimization process. +It has type "struct" and contains the following fields. +<itemizedlist> +<listitem>output.iterations: The number of iterations performed during the search</listitem> +</itemizedlist> + </para> + <para> </para> </refsection> |