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Diffstat (limited to 'help')
| -rw-r--r-- | help/intfminbnd.xml | 185 | ||||
| -rw-r--r-- | help/intfminunc.xml | 170 | ||||
| -rw-r--r-- | help/intqpipopt.xml | 127 | ||||
| -rw-r--r-- | help/master_help.xml | 23 |
4 files changed, 505 insertions, 0 deletions
diff --git a/help/intfminbnd.xml b/help/intfminbnd.xml new file mode 100644 index 0000000..8ff8004 --- /dev/null +++ b/help/intfminbnd.xml @@ -0,0 +1,185 @@ +<?xml version="1.0" encoding="UTF-8"?> + +<!-- + * + * This help file was generated from intfminbnd.sci using help_from_sci(). + * + --> + +<refentry version="5.0-subset Scilab" xml:id="intfminbnd" xml:lang="en" + xmlns="http://docbook.org/ns/docbook" + xmlns:xlink="http://www.w3.org/1999/xlink" + xmlns:svg="http://www.w3.org/2000/svg" + xmlns:ns3="http://www.w3.org/1999/xhtml" + xmlns:mml="http://www.w3.org/1998/Math/MathML" + xmlns:scilab="http://www.scilab.org" + xmlns:db="http://docbook.org/ns/docbook"> + + <refnamediv> + <refname>intfminbnd</refname> + <refpurpose>Solves a multi-variable optimization problem on a bounded interval</refpurpose> + </refnamediv> + + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> + xopt = intfminbnd(f,intcon,x1,x2) + xopt = intfminbnd(f,intcon,x1,x2,options) + [xopt,fopt] = intfminbnd(.....) + [xopt,fopt,exitflag]= intfminbnd(.....) + [xopt,fopt,exitflag,output]=intfminbnd(.....) + [xopt,fopt,exitflag,gradient,hessian]=intfminbnd(.....) + + </synopsis> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>f :</term> + <listitem><para> a function, representing the objective function of the problem</para></listitem></varlistentry> + <varlistentry><term>x1 :</term> + <listitem><para> a vector, containing the lower bound of the variables.</para></listitem></varlistentry> + <varlistentry><term>x2 :</term> + <listitem><para> a vector, containing the upper bound of the variables.</para></listitem></varlistentry> + <varlistentry><term>intcon :</term> + <listitem><para> a vector of integers, represents which variables are constrained to be integers</para></listitem></varlistentry> + <varlistentry><term>options :</term> + <listitem><para> a list, containing the option for user to specify. See below for details.</para></listitem></varlistentry> + <varlistentry><term>xopt :</term> + <listitem><para> a vector of doubles, containing the the computed solution of the optimization problem.</para></listitem></varlistentry> + <varlistentry><term>fopt :</term> + <listitem><para> a scalar of double, containing the the function value at x.</para></listitem></varlistentry> + <varlistentry><term>exitflag :</term> + <listitem><para> a scalar of integer, containing the flag which denotes the reason for termination of algorithm. See below for details.</para></listitem></varlistentry> + <varlistentry><term>gradient :</term> + <listitem><para> a vector of doubles, containing the Objective's gradient of the solution.</para></listitem></varlistentry> + <varlistentry><term>hessian :</term> + <listitem><para> a matrix of doubles, containing the Objective's hessian of the solution.</para></listitem></varlistentry> + </variablelist> +</refsection> + +<refsection> + <title>Description</title> + <para> +Search the minimum of a multi-variable function on bounded interval specified by : +Find the minimum of f(x) such that + </para> + <para> +<latex> +\begin{eqnarray} +&\mbox{min}_{x} +& f(x)\\ +& \text{subject to} & x1 \ < x \ < x2 \\ +\end{eqnarray} +</latex> + </para> + <para> +The routine calls Bonmin for solving the Bounded Optimization problem, Bonmin is a library written in C++. + </para> + <para> +The options allows the user to set various parameters of the Optimization problem. +It should be defined as type "list" and contains the following fields. +<itemizedlist> +<listitem>Syntax : options= list("IntegerTolerance", [---], "MaxNodes",[---], "MaxIter", [---], "AllowableGap",[---] "CpuTime", [---],"gradobj", "off", "hessian", "off" );</listitem> +<listitem>IntegerTolerance : a Scalar, a number with that value of an integer is considered integer..</listitem> +<listitem>MaxNodes : a Scalar, containing the Maximum Number of Nodes that the solver should search.</listitem> +<listitem>CpuTime : a Scalar, containing the Maximum amount of CPU Time that the solver should take.</listitem> +<listitem>AllowableGap : a Scalar, to stop the tree search when the gap between the objective value of the best known solution is reached.</listitem> +<listitem>MaxIter : a Scalar, containing the Maximum Number of Iteration that the solver should take.</listitem> +<listitem>gradobj : a string, to turn on or off the user supplied objective gradient.</listitem> +<listitem>hessian : a Scalar, to turn on or off the user supplied objective hessian.</listitem> +<listitem>Default Values : options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'allowablegap',0,'maxiter',2147483647,'gradobj',"off",'hessian',"off")</listitem> +</itemizedlist> + </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 Bonmin documentation, go to http://www.coin-or.org/Bonmin + </para> + <para> +</para> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +//Find x in R^6 such that it minimizes: +//f(x)= sin(x1) + sin(x2) + sin(x3) + sin(x4) + sin(x5) + sin(x6) +//-2 <= x1,x2,x3,x4,x5,x6 <= 2 +//Objective function to be minimised +function y=f(x) +y=0 +for i =1:6 +y=y+sin(x(i)); +end +endfunction +//Variable bounds +x1 = [-2, -2, -2, -2, -2, -2]; +x2 = [2, 2, 2, 2, 2, 2]; +intcon = [2 3 4] +//Options +options=list("MaxIter",[1500],"CpuTime", [100]) +[x,fval] =intfminbnd(f ,intcon, x1, x2, options) +// Press ENTER to continue + + ]]></programlisting> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +//Find x in R such that it minimizes: +//f(x)= 1/x^2 +//0 <= x <= 1000 +//Objective function to be minimised +function y=f(x) +y=1/x^2; +endfunction +//Variable bounds +x1 = [0]; +x2 = [1000]; +intcon = [1]; +[x,fval,exitflag,output,lambda] =intfminbnd(f,intcon , x1, x2) +// Press ENTER to continue + + ]]></programlisting> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +//The below problem is an unbounded problem: +//Find x in R^2 such that it minimizes: +//f(x)= -[(x1-1)^2 + (x2-1)^2] +//-inf <= x1,x2 <= inf +//Objective function to be minimised +function y=f(x) +y=-((x(1)-1)^2+(x(2)-1)^2); +endfunction +//Variable bounds +x1 = [-%inf , -%inf]; +x2 = [ %inf , %inf]; +//Options +options=list("MaxIter",[1500],"CpuTime", [100]) +[x,fval,exitflag,output,lambda] =intfminbnd(f,intcon, x1, x2, options) + ]]></programlisting> +</refsection> + +<refsection> + <title>Authors</title> + <simplelist type="vert"> + <member>Harpreet Singh</member> + </simplelist> +</refsection> +</refentry> diff --git a/help/intfminunc.xml b/help/intfminunc.xml new file mode 100644 index 0000000..dd1ae3e --- /dev/null +++ b/help/intfminunc.xml @@ -0,0 +1,170 @@ +<?xml version="1.0" encoding="UTF-8"?> + +<!-- + * + * This help file was generated from intfminunc.sci using help_from_sci(). + * + --> + +<refentry version="5.0-subset Scilab" xml:id="intfminunc" xml:lang="en" + xmlns="http://docbook.org/ns/docbook" + xmlns:xlink="http://www.w3.org/1999/xlink" + xmlns:svg="http://www.w3.org/2000/svg" + xmlns:ns3="http://www.w3.org/1999/xhtml" + xmlns:mml="http://www.w3.org/1998/Math/MathML" + xmlns:scilab="http://www.scilab.org" + xmlns:db="http://docbook.org/ns/docbook"> + + <refnamediv> + <refname>intfminunc</refname> + <refpurpose>Solves a multi-variable unconstrainted optimization problem</refpurpose> + </refnamediv> + + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> + xopt = intfminunc(f,x0) + xopt = intfminunc(f,x0,intcon) + xopt = intfminunc(f,x0,intcon,options) + [xopt,fopt] = intfminunc(.....) + [xopt,fopt,exitflag]= intfminunc(.....) + [xopt,fopt,exitflag,gradient,hessian]= intfminunc(.....) + + </synopsis> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>f :</term> + <listitem><para> a function, representing the objective function of the problem</para></listitem></varlistentry> + <varlistentry><term>x0 :</term> + <listitem><para> a vector of doubles, containing the starting of variables.</para></listitem></varlistentry> + <varlistentry><term>intcon :</term> + <listitem><para> a vector of integers, represents which variables are constrained to be integers</para></listitem></varlistentry> + <varlistentry><term>options:</term> + <listitem><para> a list, containing the option for user to specify. See below for details.</para></listitem></varlistentry> + <varlistentry><term>xopt :</term> + <listitem><para> a vector of doubles, the computed solution of the optimization problem.</para></listitem></varlistentry> + <varlistentry><term>fopt :</term> + <listitem><para> a scalar of double, the function value at x.</para></listitem></varlistentry> + <varlistentry><term>exitflag :</term> + <listitem><para> a scalar of integer, containing the flag which denotes the reason for termination of algorithm. See below for details.</para></listitem></varlistentry> + <varlistentry><term>gradient :</term> + <listitem><para> a vector of doubles, containing the Objective's gradient of the solution.</para></listitem></varlistentry> + <varlistentry><term>hessian :</term> + <listitem><para> a matrix of doubles, containing the Objective's hessian of the solution.</para></listitem></varlistentry> + </variablelist> +</refsection> + +<refsection> + <title>Description</title> + <para> +Search the minimum of an unconstrained optimization problem specified by : +Find the minimum of f(x) such that + </para> + <para> +<latex> +\begin{eqnarray} +&\mbox{min}_{x} +& f(x)\\ +\end{eqnarray} +</latex> + </para> + <para> +The routine calls Bonmin for solving the Un-constrained Optimization problem, Bonmin is a library written in C++. + </para> + <para> +The options allows the user to set various parameters of the Optimization problem. +It should be defined as type "list" and contains the following fields. +<itemizedlist> +<listitem>Syntax : options= list("IntegerTolerance", [---], "MaxNodes", [---], "CpuTime", [---], "AllowableGap", [---], "MaxIter", [---]);</listitem> +<listitem>IntegerTolerance : a Scalar, containing the Integer tolerance value that the solver should take.</listitem> +<listitem>MaxNodes : a Scalar, containing the maximum nodes that the solver should make.</listitem> +<listitem>MaxIter : a Scalar, containing the Maximum Number of Iteration that the solver should take.</listitem> +<listitem>AllowableGap : a Scalar, containing the allowable gap value that the solver should take.</listitem> +<listitem>CpuTime : a Scalar, containing the Maximum amount of CPU Time that the solver should take.</listitem> +<listitem>gradobj : a string, to turn on or off the user supplied objective gradient.</listitem> +<listitem>hessian : a Scalar, to turn on or off the user supplied objective hessian.</listitem> +<listitem>Default Values : options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'allowablegap',0,'maxiter',2147483647,'gradobj',"off",'hessian',"off")</listitem> +</itemizedlist> +</itemizedlist> + </para> + <para> +The exitflag allows to know the status of the optimization which is given back by Bonmin. +<itemizedlist> +<listitem>exitflag=0 : Optimal Solution Found. </listitem> +<listitem>exitflag=1 : InFeasible Solution.</listitem> +<listitem>exitflag=2 : Output is Continuous Unbounded.</listitem> +<listitem>exitflag=3 : Limit Exceeded.</listitem> +<listitem>exitflag=4 : User Interrupt.</listitem> +<listitem>exitflag=5 : MINLP Error.</listitem> +</itemizedlist> + </para> + <para> +For more details on exitflag see the Bonmin page, go to http://www.coin-or.org/Bonmin + </para> + <para> +</para> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +//Find x in R^2 such that it minimizes the Rosenbrock function +//f = 100*(x2 - x1^2)^2 + (1-x1)^2 +//Objective function to be minimised +function y= f(x) +y= 100*(x(2) - x(1)^2)^2 + (1-x(1))^2; +endfunction +//Starting point +x0=[-1,2]; +intcon = [2] +//Options +options=list("MaxIter", [1500], "CpuTime", [500]); +//Calling +[xopt,fopt,exitflag,gradient,hessian]=intfminunc(f,x0,intcon,options) +// Press ENTER to continue + + ]]></programlisting> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +//Find x in R^2 such that the below function is minimum +//f = x1^2 + x2^2 +//Objective function to be minimised +function y= f(x) +y= x(1)^2 + x(2)^2; +endfunction +//Starting point +x0=[2,1]; +intcon = [1]; +[xopt,fopt]=intfminunc(f,x0,intcon) +// Press ENTER to continue + + ]]></programlisting> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ +//The below problem is an unbounded problem: +//Find x in R^2 such that the below function is minimum +//f = - x1^2 - x2^2 +//Objective function to be minimised +function [y,g,h] = f(x) +y = -x(1)^2 - x(2)^2; +g = [-2*x(1),-2*x(2)]; +h = [-2,0;0,-2]; +endfunction +//Starting point +x0=[2,1]; +intcon = [1] +options = list("gradobj","ON","hessian","on"); +[xopt,fopt,exitflag,gradient,hessian]=intfminunc(f,x0,intcon,options) + ]]></programlisting> +</refsection> +</refentry> diff --git a/help/intqpipopt.xml b/help/intqpipopt.xml new file mode 100644 index 0000000..ab4f3b9 --- /dev/null +++ b/help/intqpipopt.xml @@ -0,0 +1,127 @@ +<?xml version="1.0" encoding="UTF-8"?> + +<!-- + * + * This help file was generated from intqpipopt.sci using help_from_sci(). + * + --> + +<refentry version="5.0-subset Scilab" xml:id="intqpipopt" xml:lang="en" + xmlns="http://docbook.org/ns/docbook" + xmlns:xlink="http://www.w3.org/1999/xlink" + xmlns:svg="http://www.w3.org/2000/svg" + xmlns:ns3="http://www.w3.org/1999/xhtml" + xmlns:mml="http://www.w3.org/1998/Math/MathML" + xmlns:scilab="http://www.scilab.org" + xmlns:db="http://docbook.org/ns/docbook"> + + <refnamediv> + <refname>intqpipopt</refname> + <refpurpose>Solves a linear quadratic problem.</refpurpose> + </refnamediv> + + +<refsynopsisdiv> + <title>Calling Sequence</title> + <synopsis> + xopt = intqpipopt(H,f) + xopt = intqpipopt(H,f,intcon) + xopt = intqpipopt(H,f,intcon,A,b) + xopt = intqpipopt(H,f,intcon,A,b,Aeq,beq) + xopt = intqpipopt(H,f,intcon,A,b,Aeq,beq,lb,ub) + xopt = intqpipopt(H,f,intcon,A,b,Aeq,beq,lb,ub,x0) + xopt = intqpipopt(H,f,intcon,A,b,Aeq,beq,lb,ub,x0,"path/to/bonmin_options_file") + [xopt,fopt,exitflag,output] = intqpipopt( ... ) + + </synopsis> +</refsynopsisdiv> + +<refsection> + <title>Parameters</title> + <variablelist> + <varlistentry><term>H :</term> + <listitem><para> a symmetric matrix of double, represents coefficients of quadratic in the quadratic problem.</para></listitem></varlistentry> + <varlistentry><term>f :</term> + <listitem><para> a vector of double, represents coefficients of linear in the quadratic problem</para></listitem></varlistentry> + <varlistentry><term>intcon :</term> + <listitem><para> a vector of integers, represents which variables are constrained to be integers</para></listitem></varlistentry> + <varlistentry><term>A :</term> + <listitem><para> a matrix of double, represents the linear coefficients in the inequality constraints A⋅x ≤ b.</para></listitem></varlistentry> + <varlistentry><term>b :</term> + <listitem><para> a vector of double, represents the linear coefficients in the inequality constraints A⋅x ≤ b.</para></listitem></varlistentry> + <varlistentry><term>Aeq :</term> + <listitem><para> a matrix of double, represents the linear coefficients in the equality constraints Aeq⋅x = beq.</para></listitem></varlistentry> + <varlistentry><term>beq :</term> + <listitem><para> a vector of double, represents the linear coefficients in the equality constraints Aeq⋅x = beq.</para></listitem></varlistentry> + <varlistentry><term>lb :</term> + <listitem><para> a vector of double, contains lower bounds of the variables.</para></listitem></varlistentry> + <varlistentry><term>ub :</term> + <listitem><para> a vector of double, contains upper bounds of the variables.</para></listitem></varlistentry> + <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 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 value of the function at x.</para></listitem></varlistentry> + <varlistentry><term>exitflag :</term> + <listitem><para> The exit status. See below for details.</para></listitem></varlistentry> + <varlistentry><term>output :</term> + <listitem><para> The structure consist of statistics about the optimization. See below for details.</para></listitem></varlistentry> + </variablelist> +</refsection> + +<refsection> + <title>Description</title> + <para> +Search the minimum of a constrained linear quadratic optimization problem specified by : + </para> + <para> +<latex> +\begin{eqnarray} +&\mbox{min}_{x} +& 1/2⋅x^T⋅H⋅x + f^T⋅x \\ +& \text{subject to} & A⋅x \leq b \\ +& & Aeq⋅x = beq \\ +& & lb \leq x \leq ub \\ +& & x_i \in \!\, \mathbb{Z}, i \in \!\, intcon\\ +\end{eqnarray} +</latex> + </para> + <para> +The routine calls Bonmin for solving the quadratic problem, Bonmin is a library written in C++. + </para> + <para> +The exitflag allows to know the status of the optimization which is given back by Bonmin. +<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 Bonmin page, go to http://www.coin-or.org/Bonmin + </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.constrviolation: The max-norm of the constraint violation.</listitem> +</itemizedlist> + </para> + <para> + </para> + <para> +</para> +</refsection> + +<refsection> + <title>Examples</title> + <programlisting role="example"><![CDATA[ + ]]></programlisting> +</refsection> +</refentry> diff --git a/help/master_help.xml b/help/master_help.xml new file mode 100644 index 0000000..03faed7 --- /dev/null +++ b/help/master_help.xml @@ -0,0 +1,23 @@ +<?xml version="1.0" encoding="UTF-8"?> +<!DOCTYPE book [ +<!--Begin Entities--> +<!ENTITY ab8f5d2367aea696b1bfffd29426e0c75 SYSTEM "/home/pranav/intqpipopt/help/intqpipopt.xml"> +<!--End Entities--> +]> +<book version="5.0-subset Scilab" xml:lang="en_US" + xmlns="http://docbook.org/ns/docbook" + xmlns:xlink="http://www.w3.org/1999/xlink" + xmlns:xi="http://www.w3.org/2001/XInclude" + xmlns:svg="http://www.w3.org/2000/svg" + xmlns:mml="http://www.w3.org/1998/Math/MathML" + xmlns:html="http://www.w3.org/1999/xhtml" + xmlns:db="http://docbook.org/ns/docbook"> + <info xml:id='fossee_scilab_intqpipopt_manual'> + <title>FOSSEE_Scilab_intqpipopt</title> + </info> + +<part xml:id='section_9415031c3daa4a8a181e47daa1338f51'> +<title>FOSSEE_Scilab_intqpipopt</title> +&ab8f5d2367aea696b1bfffd29426e0c75; +</part> +</book> |