You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: Rundeopt.m
    path of file: ./repos/BTCpredictor
    
    the code of the file until where you have to start completion: %********************************************************************
% Script file for the initialization and run of the differential 
% evolution optimizer.
%********************************************************************
clc;


% F_VTR		"Value To Reach" (stop when ofunc < F_VTR)
		F_VTR = -1000000; 

% I_D		number of parameters of the objective function 
		I_D = 5; 

% FVr_minbound,FVr_maxbound   vector of lower and bounds of initial population
%    		the algorithm seems to work especially well if [FVr_minbound,FVr_maxbound] 
%    		covers the region where the global minimum is expected
%               *** note: these are no bound constraints!! ***
      FVr_minbound = [0 0 0 0 0]; 
      FVr_maxbound = [1 1 1 1 1]; 
%       FVr_minbound = [10 0.25 0.25]; 
%       FVr_maxbound = [200 0.75 0.75]; 
      I_bnd_constr = 0;  %1: use bounds as bound constraints, 0: no bound constraints      
            
% I_NP            number of population members
		I_NP = 10*I_D;  %pretty high number - needed for demo purposes only

% I_itermax       maximum number of iterations (generations)
		I_itermax = 200; 
       
% F_weight        DE-stepsize F_weight ex [0, 2]
		F_weight = 0.8; 

% F_CR            crossover probabililty constant ex [0, 1]
		F_CR = 0.9; 

% I_strategy     1 --> DE/rand/1:
%                      the classical version of DE.
%      
    
function 
		I_D = 5; 

% FVr_minbound,FVr_maxbound   vector of lower and bounds of initial population
%    		the algorithm seems to work especially well if [FVr_minbound,FVr_maxbound] 
%    		covers the region where the global minimum is expected
%               *** note: these are no bound constraints!! ***
      FVr_minbound = [0 0 0 0 0]; 
      FVr_maxbound = [1 1 1 1 1]; 
%       FVr_minbound = [10 0.25 0.25]; 
%       FVr_maxbound = [200 0.75 0.75]; 
      I_bnd_constr = 0;  %1: use bounds as bound constraints, 0: no bound constraints      
            
% I_NP            number of population members
		I_NP = 10*I_D;  %pretty high number - needed for demo purposes only

% I_itermax       maximum number of iterations (generations)
		I_itermax = 200; 
       
% F_weight        DE-stepsize F_weight ex [0, 2]
		F_weight = 0.8; 

% F_CR            crossover probabililty constant ex [0, 1]
		F_CR = 0.9; 

% I_strategy     1 --> DE/rand/1:
%                      the classical version of DE.
%                2 --> DE/local-to-best/1:
%                      a version which has been used by quite a number
%                      of scientists. Attempts a balance between robustness
%                      and fast convergence.
%                3 --> DE/best/1 with jitter:
%                      taylored for small population sizes and fast convergence.
%                      Dimensionality should not be too high.
%                4 --> DE/rand/1 with per-vector-dither:
%                      Classical DE with dither to become even more robust.
%                5 --> DE/rand/1 with per-generation-dither:
%                      Classical DE with dither to become even more robust.
%                      Choosing F_weight = 0.3 is a good start here.
%                6 --> DE/rand/1 either-or-algorithm:
%                      Alternates between differential mutation and three-point-
%                      recombination.           

		I_strategy = 2;

% I_refresh     intermediate output will be produced after "I_refresh"
%               iterations. No intermediate output will be produced
%               if I_refresh is < 1
      I_refresh = 0; 
      
% I_plotting    Will use plotting if set to 1. Will skip plotting otherwise.
      I_plotting = 0;
      
%-----Problem dependent constant values for plotting----------------

if (I_plotting == 1)
   FVc_xx = [-3:0.25:3]';
   FVc_yy = [-3:0.25:3]';

   [FVr_x,FM_y]=meshgrid(FVc_xx',FVc_yy') ;
   FM_meshd = peaks(FVr_x,FM_y); 

   S_struct.FVc_xx    = FVc_xx;
   S_struct.FVc_yy    = FVc_yy;
   S_struct.FM_meshd  = FM_meshd; 
end