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+<?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,options)
+   xopt = intqpipopt(H,f,intcon,A,b,Aeq,beq,lb,ub,x0,options,"file_path")
+   [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>options :</term>
+      <listitem><para> a list containing the parameters to be set.</para></listitem></varlistentry>
+   <varlistentry><term>file_path :</term>
+      <listitem><para> path to bonmin opt file if used.</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 : 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>
+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>
+</refsection>
+
+<refsection>
+   <title>Examples</title>
+   <programlisting role="example"><![CDATA[
+H = [1 -1; -1 2];
+f = [-2; -6];
+A = [1 1; -1 2; 2 1];
+b = [2; 2; 3];
+lb=[0,0];
+ub=[%inf, %inf];
+intcon = [1 2];
+[xopt,fopt,status,output]=intqpipopt(H,f,intcon,A,b,[],[],lb,ub)
+
+   ]]></programlisting>
+</refsection>
+
+<refsection>
+   <title>Examples</title>
+   <programlisting role="example"><![CDATA[
+//Find x in R^6 such that:
+Aeq= [1,-1,1,0,3,1;
+-1,0,-3,-4,5,6;
+2,5,3,0,1,0];
+beq=[1; 2; 3];
+A= [0,1,0,1,2,-1;
+-1,0,2,1,1,0];
+b = [-1; 2.5];
+lb=[-1000; -10000; 0; -1000; -1000; -1000];
+ub=[10000; 100; 1.5; 100; 100; 1000];
+x0 = repmat(0,6,1);
+param = list("MaxIter", 300, "CpuTime", 100);
+//and minimize 0.5*x'*H*x + f'*x with
+f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
+intcon = [2 4];
+[xopt,fopt,exitflag,output]=intqpipopt(H,f,intcon,A,b,Aeq,beq,lb,ub,x0,param)
+   ]]></programlisting>
+</refsection>
+
+<refsection>
+   <title>Authors</title>
+   <simplelist type="vert">
+   <member>Akshay Miterani and Pranav Deshpande</member>
+   </simplelist>
+</refsection>
+</refentry>