initial add

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}
+&amp;\mbox{min}_{x}
+&amp; f(x)\\
+&amp; \text{subject to} &amp; x1 \ &lt; x \ &lt; 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}
+&amp;\mbox{min}_{x}
+&amp; 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}
+&amp;\mbox{min}_{x}
+&amp; 1/2⋅x^T⋅H⋅x + f^T⋅x  \\
+&amp; \text{subject to} &amp; A⋅x \leq b \\
+&amp; &amp; Aeq⋅x = beq \\
+&amp; &amp; lb \leq x \leq ub \\
+&amp; &amp; 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>