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diff --git a/help/en_US/qpipopt_mat.xml b/help/en_US/qpipopt_mat.xml deleted file mode 100644 index 7dec2b1..0000000 --- a/help/en_US/qpipopt_mat.xml +++ /dev/null @@ -1,142 +0,0 @@ -<?xml version="1.0" encoding="UTF-8"?> - -<!-- - * - * This help file was generated from qpipopt_mat.sci using help_from_sci(). - * - --> - -<refentry version="5.0-subset Scilab" xml:id="qpipopt_mat" 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>qpipopt_mat</refname> - <refpurpose>Solves a linear quadratic problem.</refpurpose> - </refnamediv> - - -<refsynopsisdiv> - <title>Calling Sequence</title> - <synopsis> - xopt = qpipopt_mat(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) - x = qpipopt_mat(H,f) - x = qpipopt_mat(H,f,A,b) - x = qpipopt_mat(H,f,A,b,Aeq,beq) - x = qpipopt_mat(H,f,A,b,Aeq,beq,lb,ub) - [xopt,fopt,exitflag,output,lamda] = qpipopt_mat( ... ) - - </synopsis> -</refsynopsisdiv> - -<refsection> - <title>Parameters</title> - <variablelist> - <varlistentry><term>H :</term> - <listitem><para> a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.</para></listitem></varlistentry> - <varlistentry><term>f :</term> - <listitem><para> a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem</para></listitem></varlistentry> - <varlistentry><term>A :</term> - <listitem><para> a m x n matrix of doubles, represents the linear coefficients in the inequality constraints</para></listitem></varlistentry> - <varlistentry><term>b :</term> - <listitem><para> a column vector of doubles, represents the linear coefficients in the inequality constraints</para></listitem></varlistentry> - <varlistentry><term>Aeq :</term> - <listitem><para> a meq x n matrix of doubles, represents the linear coefficients in the equality constraints</para></listitem></varlistentry> - <varlistentry><term>beq :</term> - <listitem><para> a vector of doubles, represents the linear coefficients in the equality constraints</para></listitem></varlistentry> - <varlistentry><term>LB :</term> - <listitem><para> a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.</para></listitem></varlistentry> - <varlistentry><term>UB :</term> - <listitem><para> a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.</para></listitem></varlistentry> - <varlistentry><term>xopt :</term> - <listitem><para> a nx1 matrix of doubles, the computed solution of the optimization problem.</para></listitem></varlistentry> - <varlistentry><term>fopt :</term> - <listitem><para> a 1x1 matrix of doubles, the function value at x.</para></listitem></varlistentry> - <varlistentry><term>exitflag :</term> - <listitem><para> Integer identifying the reason the algorithm terminated.</para></listitem></varlistentry> - <varlistentry><term>output :</term> - <listitem><para> Structure containing information about the optimization.</para></listitem></varlistentry> - <varlistentry><term>lambda :</term> - <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).</para></listitem></varlistentry> - </variablelist> -</refsection> - -<refsection> - <title>Description</title> - <para> -Search the minimum of a constrained linear quadratic optimization problem specified by : -find the minimum of f(x) such that - </para> - <para> -<latex> -\begin{eqnarray} -&\mbox{min}_{x} -& 1/2*x'*H*x + f'*x \\ -& \text{subject to} & A.x \leq b \\ -& & Aeq.x \leq beq \\ -& & lb \leq x \leq ub \\ -\end{eqnarray} -</latex> - </para> - <para> -We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by Andreas Wächter and Carl Laird. - </para> - <para> -</para> -</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]; -//and minimize 0.5*x'*Q*x + p'*x with -f=[1; 2; 3; 4; 5; 6]; H=eye(6,6); -[xopt,fopt,exitflag,output,lambda]=qpipopt_mat(H,f,A,b,Aeq,beq,lb,ub) -clear H f A b Aeq beq lb ub; - - ]]></programlisting> -</refsection> - -<refsection> - <title>Examples</title> - <programlisting role="example"><![CDATA[ -//Find the value of x that minimize following function -// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 -// Subject to: -// x1 + x2 ≤ 2 -// –x1 + 2x2 ≤ 2 -// 2x1 + x2 ≤ 3 -// 0 ≤ x1, 0 ≤ x2. -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]; -[xopt,fopt,exitflag,output,lambda] = qpipopt_mat(H,f,A,b,[],[],lb,ub) - - ]]></programlisting> -</refsection> - -<refsection> - <title>Authors</title> - <simplelist type="vert"> - <member>Keyur Joshi, Saikiran, Iswarya, Harpreet Singh</member> - </simplelist> -</refsection> -</refentry> |