CodeMode.m

%*********************************EDOLAB ver 2.00*********************************
%
% Authors: Mai Peng and Danial Yazdani
% e-mails: pengmai1998@gmail.com
%          danial.yazdani@gmail.com
% Last Edited: Nov 22, 2025
%
% ------------
% Reference:
% ------------
%
%  Title: "EDOLAB: An Open-Source Platform for Education and Experimentation with Evolutionary Dynamic Optimization Algorithms"
%  ArXiv: arxiv.org/abs/2308.12644
%  Note: reference information will be completed after acceptance of the paper
%
% ------------
% Notification:
% ------------
% 
%  This function is used to run EDOLAB without GUI
%
% --------
% License:
% --------
% This program is to be used under the terms of the GNU General Public License
% (http://www.gnu.org/copyleft/gpl.html).
% e-mail: danial DOT yazdani AT gmail DOT com
% Copyright notice: (c) 2023 Danial Yazdani
%*********************************************************************************
clear all;close all;clc;
%% Add the full path of EDOLAB folder and its subfolders into MATLAB's work space
nowPath = mfilename('fullpath');
projectPath = nowPath(1:max(strfind(nowPath,'\'))-1);
allPaths = genpath(projectPath);
pathsToAdd = regexprep(allPaths, '[^;]*OctaveVersion[^;]*;?', '');
addpath(pathsToAdd);
%% ********Selecting Algorithm & Benchmark********
AlgorithmName = 'ACFPSO';    %Please input the name of algorithm (EADO) you want to run here (names are case sensitive).
%  The list of algorithms (EADOs) and some of their details can be found in Table 1 of the EDOLAB's paper.
%  The current version of EDOLAB includes the following algorithms (EADOs):
%  'ACFPSO' , 'AMPDE' , 'AMPPSO' , 'AmQSO' , 'AMSO' , 'CDE' , 'CESO', 'CPSO' , 'CPSOR' 
%  'DSPSO' , 'DynDE' , 'DynPopDE' , 'FTMPSO' , 'HmSO' ,  'IDSPSO' , 'ImQSO' , 'mCMAES'
%  'mDE' , 'mjDE' , 'mPSO' , 'mQSO' , 'psfNBC' , 'RPSO' , 'SPSO_AP_AD' ,
%  'TMIPSO', 'DPCPSO', 'APCPSO'
BenchmarkName = 'GMPB';     %Please input the name of benchmark you want to use here (names are case sensitive).
%  The current version of EDOLAB includes the following benchmark generators: 'MPB' , 'GDBG' , 'GMPB' , 'FPs'
%% Get the algorithm and benchmark lists
AlgorithmsFloder = dir([projectPath,'\Algorithm']);
AlgorithmsList = repmat("",length(AlgorithmsFloder)-2,1);
for i = 3:length(AlgorithmsFloder)
    AlgorithmsList(i-2,1) = AlgorithmsFloder(i).name;
end
BenchmarksFloder = dir([projectPath,'\Benchmark']);
BenchmarksList = repmat("",length(BenchmarksFloder)-5,1);
BenchmarksCount = 0;
for i = 3:length(BenchmarksFloder)
    if(isempty(strfind(BenchmarksFloder(i).name,'.m')))
        BenchmarksCount = BenchmarksCount + 1;
        BenchmarksList(BenchmarksCount,1) = BenchmarksFloder(i).name;
    end
end
if(~ismember(AlgorithmName,AlgorithmsList))
    error("No Such Algorithm in EDOLAB");
elseif(~ismember(BenchmarkName,BenchmarksList))
    error("No Such Benchmark in EDOLAB");
end
%% ********Algorithm parameters, Benchmark parameters and Run number********
% Configuration workflow (for Code Mode users):
%  1) Default parameter definitions (do not require JSON):
%     - Algorithm settings: Algorithm/<AlgorithmName>/getAlgConfigurableParameters_<AlgorithmName>.m
%     - Problem  settings: Benchmark/<BenchmarkName>/getProConfigurableParameters_<BenchmarkName>.m
%     In these files, all configurable parameters are defined as:
%       ConfigurableParameters.<ParamName>.value
%
%     To discover available parameter names, either:
%       - Open the corresponding getAlgConfigurableParameters_*.m / getProConfigurableParameters_*.m
%         files and inspect the fields of ConfigurableParameters; or
%       - In MATLAB Command Window, run:
%             tmpAlg = getAlgConfigurableParameters(AlgorithmName);
%             fieldnames(tmpAlg)
%             tmpPro  = getProConfigurableParameters(BenchmarkName);
%             fieldnames(tmpPro)
%         then use these field names below.
%
%  2) Quick override in CodeMode.m (for fast experiments):
%     First load the default configuration:
ConfigurableAlgParameters = getAlgConfigurableParameters(AlgorithmName);
ConfigurableProParameters = getProConfigurableParameters(BenchmarkName);
%     Then optionally override any parameter *for this run only* by assigning:
%       ConfigurableAlgParameters.<ParamName>.value  = <new value>;
%       ConfigurableProParameters.<ParamName>.value  = <new value>;
%     For example (uncomment and adjust as needed):
%       % Algorithm (ACFPSO) example:
%       % ConfigurableAlgParameters.PopulationSize.value      = 20;
%       % ConfigurableAlgParameters.c1.value                  = 1.8;
%       % ConfigurableAlgParameters.c2.value                  = 1.6;
%       %
%       % Benchmark (GMPB) example:
%       % ConfigurableProParameters.Dimension.value           = 10;
%       % ConfigurableProParameters.ChangeFrequency.value     = 2000;
%       % ConfigurableProParameters.PeakNumber.value          = 5;
%
%     Changes here do not modify GUI or JSON files; they only affect the current CodeMode run.
Dimension                      = ConfigurableProParameters.Dimension.value;
RunNumber                      = 1;   %It should be set to 31 in Experimentation module, and must be set to 2 for using Education module.
%% ********Figures and Outputs********
GeneratingExcelFile            = 1;   %Set to 1 (only for using the Experimentation module) to save the output statistics in an Excel file (in the Results folder), 0 otherwise. 
OutputFig                      = 1;   %Set to 1 (only for using the Experimentation module) to draw offline error over time and current error plot, 0 otherwise.
VisualizationOverOptimization  = 0;   %Set to 1 for using the Education module, 0 otherwise. This must be set to 0 if the user intends to use the Experimentation module.
%If VisualizationOverOptimization is set to 1, it means that EDOLAB enters its Education module. 
%To enter the Education module, RunNumber must be set to 1, Dimension must be set to 2, and no excel file or output figure is generated. 
%If the user does not intend to use the Education module, she or he must set VisualizationOverOptimization to 0. 
%EDOLAB changes the aforementioned parameters based on the requirements of the Education module if VisualizationOverOptimization is set to 1.
if VisualizationOverOptimization==1%Forcing the right values for the following parameters when using the Education module.  
    if Dimension~=2 || RunNumber~=1 || GeneratingExcelFile~=0 || OutputFig~= 0
       warning('By setting VisualizationOverOptimization to 1, you have chosen to use the Education module of EDOLAB; therefore, run number and dimension are set to 1 and 2, respectively. The output figure and Excel file are disabled.');      
    end
    ConfigurableProParameters.Dimension.value                  = 2;   
    RunNumber                                                  = 1;
    GeneratingExcelFile                                        = 0;   
    OutputFig                                                  = 0;
end
%% Running the chosen algorithm (EDOA) on the chosen benchmark
main_EDO = str2func(['main_',AlgorithmName]);
ProgressInfo = struct('IsParallel', false);
[Problem,Results,CurrentError,VisualizationInfo,Iteration] = main_EDO(VisualizationOverOptimization, RunNumber, BenchmarkName, ConfigurableProParameters, ConfigurableAlgParameters, ProgressInfo);
%% Output
close;clc;
fields = fieldnames(Results);
for i = 1:numel(fields)
    name = fields{i};
    if strcmp(name, 'T_r')
        continue; % Runtime is reported separately below
    end
    info = Results.(name);   
    if isfield(info, 'mean') && isfield(info, 'median') && isfield(info, 'StdErr')
        disp([name, ' ==> Mean = ', num2str(info.mean), ', Median = ', num2str(info.median), ', Standard Error = ', num2str(info.StdErr)]);
    end
end

% Runtime report (not used as a comparison indicator)
if isfield(Results, 'T_r')
    T_r = Results.T_r;
    disp('Runtime (T_r):');
    disp(['  Mean   = ', num2str(T_r.mean)]);
    disp(['  Median = ', num2str(T_r.median)]);
    disp(['  StdErr = ', num2str(T_r.StdErr)]);
    if isfield(T_r, 'AllResults')
        disp(['  All runs (s): ', num2str(T_r.AllResults)]);
    end
end

% Generating an Excel file containing output statistics (only for the Experimentation module)
if GeneratingExcelFile==1
    OutputDetailResultsToExcel(AlgorithmName, ConfigurableAlgParameters, BenchmarkName, ConfigurableProParameters, Results, [projectPath,'\Results\TaskDetailResults']);
end
% Generating an output figure containing offline error and current error plots (only for the Experimentation module)
if OutputFig==1
    OutputPlot(CurrentError,RunNumber,Results.E_o,Results.E_bbc,AlgorithmName);
end
% Generating over-time figures for Education module
if (VisualizationOverOptimization==1)
    OutputEducationalFigures(Iteration,ConfigurableProParameters.PeakNumber.value,VisualizationInfo,CurrentError,Problem);
end