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diff --git a/newstructure/help/en_US/intfminunc.xml b/newstructure/help/en_US/intfminunc.xml deleted file mode 100644 index ce55272..0000000 --- a/newstructure/help/en_US/intfminunc.xml +++ /dev/null @@ -1,170 +0,0 @@ -<?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 an unconstrainted multi-variable mixed integer non linear programming 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 a multi-variable mixed integer non linear programming unconstrained optimization problem specified by : -Find the minimum of f(x) such that - </para> - <para> -<latex> -\begin{eqnarray} -&\mbox{min}_{x} -& f(x) -& x_i \in \!\, \mathbb{Z}, i \in \!\, I -\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> - </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> |