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-// Copyright (C) 2015 - IIT Bombay - FOSSEE
-//
-// This file must be used under the terms of the CeCILL.
-// This source file is licensed as described in the file COPYING, which
-// you should have received as part of this distribution.  The terms
-// are also available at
-// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
-// Author: Harpreet Singh, Pranav Deshpande and Akshay Miterani
-// Organization: FOSSEE, IIT Bombay
-// Email: toolbox@scilab.in
-
-function [xopt,fopt,exitflag,gradient,hessian] = intfminunc (varargin)
-	// Solves an unconstrainted multi-variable mixed integer non linear programming optimization problem
-	//
-	//   Calling Sequence
-	//   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(.....)
-	//
-	//   Parameters
-	//   f : a function, representing the objective function of the problem 
-	//   x0 : a vector of doubles, containing the starting of variables.
-	//	 intcon : a vector of integers, represents which variables are constrained to be integers
-	//   options: a list, containing the option for user to specify. See below for details.
-	//   xopt : a vector of doubles, the computed solution of the optimization problem.
-	//   fopt : a scalar of double, the function value at x. 
-	//   exitflag : a scalar of integer, containing the flag which denotes the reason for termination of algorithm. See below for details.
-	//   gradient : a vector of doubles, containing the Objective's gradient of the solution.
-	//   hessian  : a matrix of doubles, containing the Objective's hessian of the solution.
-	//
-	//   Description
-	//   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 
-	//
-	//   <latex>
-	//    \begin{eqnarray}
-	//    &\mbox{min}_{x}
-	//    & f(x)
-	//    & x_i \in \!\, \mathbb{Z}, i \in \!\, I
-	//    \end{eqnarray}
-	//   </latex>
-	//
-	//   The routine calls Bonmin for solving the Un-constrained Optimization problem, Bonmin is a library written in C++.
-	//
-	// 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>
-	//
-	// 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>
-	//
-	// For more details on exitflag see the Bonmin page, go to http://www.coin-or.org/Bonmin
-	//
-	// Examples
-	//     //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
-	//
-	// Examples
-	//      //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
-	//
-	// Examples
-	//     //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)
-
-	//To check the number of input and output arguments
-   	[lhs , rhs] = argn();
-	
-	//To check the number of arguments given by the user
-   	if ( rhs<2 | rhs>4 ) then
-    		errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be int [2 3 4] "), "intfminunc", rhs);
-    		error(errmsg);
-   	end
- 
-	//Storing the 1st and 2nd Input Parameters  
-   	fun = varargin(1);
-   	x0 = varargin(2);
-   //To add intcon
-   intcon=[];
-   if ( rhs >=3 ) then
-			intcon = varargin(3);
-	end
-
-  param = list();
-  //To check whether options has been entered by user   
- 	if ( rhs>=4  ) then
-      param =varargin(4);
- 	end
-  
-  nbvar = size(x0,"*");
-
-  ///////////////// To check whether the Input arguments /////////////////
-  Checktype("intfminunc", fun, "fun", 1, "function");
-  Checktype("intfminunc", x0, "x0", 2, "constant");
-  Checktype("intfminunc", intcon, "intcon", 3, "constant");
-  Checktype("intfminunc", param, "options", 4, "list");  
-  
-  ///////////////// To check x0 ///////////////// 
-  Checkvector("intfminunc", x0, "x0", 2, nbvar)
-  x0 = x0(:);
-  Checkvector("intfminbnd", intcon, "intcon", 3, size(intcon,"*"))
-  intcon = intcon(:);
-
-  //Error Checks for intcon 
-  for i=1:size(intcon,1)
-      if(intcon(i)>nbvar) then
-        errmsg = msprintf(gettext("%s: The values inside intcon should be less than the number of variables"), "intfminunc");
-        error(errmsg);
-      end
-
-      if (intcon(i)<0) then
-        errmsg = msprintf(gettext("%s: The values inside intcon should be greater than 0 "), "intfminunc");
-        error(errmsg);
-      end
-
-      if(modulo(intcon(i),1)) then
-        errmsg = msprintf(gettext("%s: The values inside intcon should be an integer "), "intfminunc");
-        error(errmsg);
-      end
-  end
-   
-  //If options has been entered, then check whether an even number of entires has been entered   
-  if (modulo(size(param),2)) then
-    errmsg = msprintf(gettext("%s: Size of parameters should be even"), "intfminunc");
-    error(errmsg);
-  end 
-   
-  intconSize = length(intcon);
-  
-  options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'allowablegap',0,'maxiter',2147483647,'gradobj',"off",'hessian', "off")
-
-  //Pushing param into default value
-  
-  for i = 1:(size(param))/2
-    select convstr(param(2*i-1),'l')
-      case 'integertolerance' then
-        Checktype("intfminbnd_options", param(2*i), param(2*i-1), 2*i, "constant");
-        options(2) = param(2*i);
-      case 'maxnodes' then
-        Checktype("intfminbnd_options", param(2*i), param(2*i-1), 2*i, "constant");
-        options(4) = options(2*i);
-      case 'cputime' then 
-        Checktype("intfminbnd_options", param(2*i), param(2*i-1), 2*i, "constant");
-        options(6) = options(2*i);
-      case 'allowablegap' then
-        Checktype("intfminbnd_options", param(2*i), param(2*i-1), 2*i, "constant");
-        options(8) = options(2*i);
-      case 'maxiter' then
-        Checktype("intfminbnd_options", param(2*i), param(2*i-1), 2*i, "constant");
-        options(10) = options(2*i);
-      case 'gradobj' then
-        Checktype("intfminbnd_options", param(2*i), param(2*i-1), 2*i, "string");
-        if(convstr(param(2*i),'l') == "on") then
-          options(12) = "on"
-        elseif(convstr(param(2*i),'l') == "off") then
-          options(12) = "off"
-        else
-          error(999, 'Unknown string passed in gradobj.');
-        end
-      case 'hessian' then
-        Checktype("intfminbnd_options", param(2*i), param(2*i-1), 2*i, "string");
-        if(convstr(param(2*i),'l') == "on") then
-          options(14) = "on";
-        elseif(convstr(param(2*i),'l') == "off") then
-          options(14) = "off";
-        else
-          error(999, 'Unknown string passed in hessian.');
-        end
-      else
-        error(999, 'Unknown string argument passed.');
-    end
-  end 
-
-  ///////////////// Functions Check /////////////////
-
-  //To check the match between fun (1st Parameter) and x0 (2nd Parameter)
-  if(execstr('init=fun(x0)','errcatch')==21) then
-    errmsg = msprintf(gettext("%s: Objective function and x0 did not match"), "intfminunc");
-    error(errmsg);
-  end
-
-  if(options(12) == "on") then
-    
-      if(execstr('[grad_y,grad_dy]=fun(x0)','errcatch')==59) then
-        errmsg = msprintf(gettext("%s: Gradient of objective function is not provided"), "intfminunc");
-        error(errmsg);
-      end
-
-      Checkvector("intfminunc_options", grad_dy, "dy", 12, nbvar);
-  end
-
-  if(options(14) == "on") then
-    
-      if(execstr('[hessian_y,hessian_dy,hessian]=fun(x0)','errcatch')==59) then
-        errmsg = msprintf(gettext("%s: Gradient of objective function is not provided"), "intfminunc");
-        error(errmsg);
-      end
-
-      if ( ~isequal(size(hessian),[nbvar nbvar]) ) then
-        errmsg = msprintf(gettext("%s: Size of hessian should be nbvar X nbvar"), "intfminunc");
-        error(errmsg);
-      end
-  end
-
-  //Converting the User defined Objective function into Required form (Error Detectable)
- 	function [y,check] = _f(x)
- 		try
-      y=fun(x)
-      [y,check] =  checkIsreal(y)
-	  catch
-		  y=0;
-		  check=1;
-	  end
-   endfunction
-    
-   //Defining an inbuilt Objective gradient function 
-    function [dy,check] = _gradf(x) 
-      if (options(12) =="on") then
-        try
-          [y,dy]=fun(x);
-          [dy,check] =  checkIsreal(dy);
-        catch
-          dy = 0;
-          check=1;
-        end
-      else
-        try 
-          dy=numderivative(fun,x);
-          [dy,check] =  checkIsreal(dy);
-        catch
-          dy=0;
-          check=1;
-        end
-      end
-    endfunction
-
-  //Defining a function to calculate Hessian if the respective user entry is OFF 
-  function [hessy,check]=_gradhess(x)
-    if (options(14) == "on") then
-      try
-        [obj,dy,hessy] = fun(x)
-        [hessy,check] =  checkIsreal(hessy)
-      catch
-        hessy = 0;
-        check=1;
-      end
-    else
-      try
-        [dy,hessy]=numderivative(fun,x)
-        [hessy,check] =  checkIsreal(hessy)
-      catch
-        hessy=0;
-        check=1;
-      end
-    end
-  endfunction
-
-    //Calling the bonmin function for solving the above problem
-	  [xopt,fopt,exitflag] = inter_fminunc(_f,_gradf,_gradhess,x0,intcon,options,intconSize,nbvar);
-
-  	//In the cases of the problem not being solved, return NULL to the output matrices
-  	if( exitflag~=0 & exitflag~=3 ) then
-  		gradient = [];
-        hessian = [];
-    else
-      [ gradient, hessian] = numderivative(_f, xopt, [], [], "blockmat");
-  	end
-
-    //To print output message
-    select exitflag
-        case 0 then
-            printf("\nOptimal Solution Found.\n");
-        case 1 then
-            printf("\nInFeasible Solution.\n");
-        case 2 then
-            printf("\nObjective Function is Continuous Unbounded.\n");
-        case 3 then
-            printf("\Limit Exceeded.\n");
-        case 4 then
-            printf("\nUser Interrupt.\n");
-        case 5 then
-            printf("\nMINLP Error.\n");
-        else
-            printf("\nInvalid status returned. Notify the Toolbox authors\n");
-            break;
-    end
-endfunction
-
-function [y, check] = checkIsreal(x)
-	if ((~isreal(x))) then
-		y = 0
-		check=1;
-	else
-        y = x;
-		check=0;
-	end	
-endfunction