cbcintlinprog added

1 files changed, 0 insertions, 360 deletions

diff --git a/newstructure/macros/intfminbnd.sci b/newstructure/macros/intfminbnd.sci
deleted file mode 100644
index 2304bbf..0000000
--- a/newstructure/macros/intfminbnd.sci
+++ /dev/null
@@ -1,360 +0,0 @@
-// 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] = intfminbnd (varargin)
-	// Solves a multi-variable mixed integer non linear programming optimization problem on a bounded interval
-	//
-	//   Calling Sequence
-	//   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(.....)
-	//
-	//   Parameters
-	//   f : a function, representing the objective function of the problem 
-	//   x1 : a vector, containing the lower bound of the variables.
-	//   x2 : a vector, containing the upper bound of the 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, containing the the computed solution of the optimization problem.
-	//   fopt : a scalar of double, containing the 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 optimization on bounded interval specified by :
-	//   Find the minimum of f(x) such that 
-	//
-	//   <latex>
-	//    \begin{eqnarray}
-	//    &\mbox{min}_{x}
-	//    & f(x)\\
-	//    & \text{subject to} & x1 \ < x \ < x2 \\
-  //    & x_i \in \!\, \mathbb{Z}, i \in \!\, I
-	//    \end{eqnarray}
-	//   </latex>
-	//
-	//   The routine calls Bonmin for solving the Bounded 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",[---], "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>
-	//
-	// 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>
-	//
-	// For more details on exitflag see the Bonmin documentation, go to http://www.coin-or.org/Bonmin
-  //
-	// Examples
-	//	//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
-	//
-	// Examples
-	//	//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
-	//
-	// Examples
-	//    //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)  
-	// Authors
-	// Harpreet Singh
-
-	//To check the number of input and output arguments
- 	[lhs , rhs] = argn();
-	
-	//To check the number of arguments given by the user
- 	if ( rhs<4 | rhs>5 ) then
-  		errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be int [4 5] "), "intfminbnd", rhs);
-  		error(errmsg);
- 	end
- 
-	//Storing the Input Parameters  
- 	fun = varargin(1);
- 	intcon = varargin(2);	
- 	x1 = varargin(3);
- 	x2 = varargin(4);
-  nbvar = size(x1,"*");
-
-  param = list();
-  //To check whether options has been entered by user   
-  if ( rhs>=5  ) then
-      param =varargin(5);
-  end
-
-  //To check whether the Input arguments
-  Checktype("intfminbnd", fun, "fun", 1, "function");
-  Checktype("intfminbnd", intcon, "intcon", 2, "constant");
-  Checktype("intfminbnd", x1, "x1", 3, "constant");
-  Checktype("intfminbnd", x2, "x2", 4, "constant");
-  Checktype("intfminbnd", param, "options", 5, "list");  
-
-
-  if(nbvar==0) then
-    errmsg = msprintf(gettext("%s: x1 cannot be an empty"), "intfminbnd");
-    error(errmsg);    
-  end
-
-  ///////////////// To check vectors ///////////////// 
-  Checkvector("intfminbnd", x1, "x1", 3, nbvar)
-  x1 = x1(:);
-  Checkvector("intfminbnd", x2, "x2", 4, nbvar)
-  x2 = x2(:);
-  Checkvector("intfminbnd", intcon, "intcon", 2, size(intcon,"*"))
-  intcon = intcon(:);
-
-  if(~isequal(size(x1),size(x2))) then
-    errmsg = msprintf(gettext("%s: x1 and x2 should be of same size"), "intfminbnd");
-    error(errmsg);
-  end
-
-  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"), "intfminbnd");
-        error(errmsg);
-      end
-
-      if (intcon(i)<0) then
-        errmsg = msprintf(gettext("%s: The values inside intcon should be greater than 0 "), "intfminbnd");
-        error(errmsg);
-      end
-
-      if(modulo(intcon(i),1)) then
-        errmsg = msprintf(gettext("%s: The values inside intcon should be an integer "), "intfminbnd");
-        error(errmsg);
-      end
-  end   
-  
-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(options(2*i),'l') == "on") then
-          options(12) = "on"
-        elseif(convstr(options(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(options(2*i),'l') == "on") then
-          options(14) = "on";
-        elseif(convstr(options(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 f (1st Parameter) and x1 (2nd Parameter)
-  if(execstr('init=fun(x1)','errcatch')==21) then
-    errmsg = msprintf(gettext("%s: Objective function and x1 did not match"), "intfminbnd");
-    error(errmsg);
-  end
-
-  if(options(12) == "on") then
-      if(execstr('[grad_y,grad_dy]=fun(x1)','errcatch')==59) then
-        errmsg = msprintf(gettext("%s: Gradient of objective function is not provided"), "intfminbnd");
-        error(errmsg);
-      end
-      Checkvector("intfminbnd_options", grad_dy, "dy", 12, nbvar);
-  end
-
-  if(options(14) == "on") then
-      if(execstr('[hessian_y,hessian_dy,hessian]=fun(x1)','errcatch')==59) then
-        errmsg = msprintf(gettext("%s: Gradient of objective function is not provided"), "intfminbnd");
-        error(errmsg);
-      end
-
-      if ( ~isequal(size(hessian) == [nbvar nbvar]) ) then
-        errmsg = msprintf(gettext("%s: Size of hessian should be nbvar X nbvar"), "intfminbnd");
-        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 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
-    
-   //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
-    
-    intconsize = size(intcon,"*");
-
-	[xopt,fopt,exitflag] = inter_fminbnd(_f,_gradf,_gradhess,x1,x2,intcon,options,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("\nnObjective 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