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@alonsovelam
alonsovelam committed May 21, 2020
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96 changes: 96 additions & 0 deletions GeneralCheck_Advanced_noDelta.m
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% % This function evaluates the instances created and determine whether % %
% % they are correct or not. For doing so, the function creates a copy % %
% % of the instance and solves it with each heuristic from the % %
% % HEURIDrepository then it follows the fitness function described in % %
% % EvaluateUPSOtoJSSP_Advanced according to the objective given while % %
% % calling the function. % %
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% % The parameters of the function are described as follows: % %
% % % %
% % folder: It is the name in quotes of the folder where the % %
% % instances are located. % %
% % heurID: It is the ID of the heuristic used to improve or % %
% % diminish 1.- LPT 2.- SPT 3.- MPA 4.- LPA % %
% % objective : 1. XvsAll 2. AllvsX % %
% % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % %
% % nbJobs : Number of Jobs of the instance to be checked; % %
% % Set to 3 % %
% % nbMachines: Number of Machines of the instance to be checked % %
% % Set to 4 % %
% % nbRep : Number of instances created for the parcticular % %
% % configuration; set to 30 % %
% % timeRanges: Range in which the operation times are set. % %
% % Set to [0 10] % %
% % % %
% % to change this use varargin(1), varargin(2), varargin(3) and % %
% % varargin(4) respectively. % % % %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


function [performanceMatrix] = GeneralCheck_Advanced_noDelta(folder,heurID, objective, varargin)

folder2 = pwd;

nbJobs = 3;
nbMachines = 4;
nbRep = 30;
timeRanges = [0 10];

if nargin == 4, nbJobs = varargin{1}; end
if nargin == 5, nbMachines = varargin{2}; end
if nargin == 6, nbRep = varargin{3}; end
if nargin == 7, timeRanges = varargin{4}; end


%Convert numeric heurID to a three letter heurID
if heurID == 1
heuristicID = "LPT";
elseif heurID == 2
heuristicID = "SPT";
elseif heurID == 3
heuristicID = "MPA";
elseif heurID == 4
heuristicID = "LPA";
end

if objective == 1
addressID = heuristicID + "vsAll_J" + num2str(nbJobs) + "xM" + num2str(nbMachines);
elseif objective == 2
addressID = "Allvs" + heuristicID + "_J" + num2str(nbJobs) + "xM" + num2str(nbMachines);
end


for NB=1:nbRep;
oldfolder= cd(folder2);
PathAddress = char(folder+"\"+addressID+"\");

if objective == 1
address= char("JSSPInstanceJ"+num2str(nbJobs)+"M"+num2str(nbMachines)+"T1"+num2str(timeRanges(1)) ...
+"T2"+num2str(timeRanges(2))+"Rep"+num2str(NB)+heuristicID+"vsAll.mat");
elseif objective == 2
address= char("JSSPInstanceJ"+num2str(nbJobs)+"M"+num2str(nbMachines)+"T1"+num2str(timeRanges(1)) ...
+"T2"+num2str(timeRanges(2))+"Rep"+num2str(NB)+"Allvs"+heuristicID +".mat");
end
%
JSSPInstance = {};
%
addpath(genpath(PathAddress));
load(address)



perfDataMatrix(NB,1) = JSSPInstance{2};


end
filename=(addressID)

oldfolder= cd(folder2);
save(filename, 'perfDataMatrix');
performanceMatrix = perfDataMatrix;
end




12 changes: 12 additions & 0 deletions HeurIDVector.m
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function[heurID2]=HeurIDVector(heurID)

if heurID == 1
heurID2 = [2 3 4];
elseif heurID == 2
heurID2 = [1 3 4];
elseif heurID == 3
heurID2 = [1 2 4];
elseif heurID == 4
heurID2 = [1 2 3];
end
end
4 changes: 4 additions & 0 deletions Histograma.m
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x=ans(:,1)

plot(x, "o")
ylim =([0 100])
73 changes: 73 additions & 0 deletions MedianCondensedHeatMaps.m
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HeurID1=[1 1 1 2 2 2 3 3 3 4 4 4];
HeurID2=[2 2 2 1 1 1 4 4 4 3 3 3];
Population= [10 30 50 10 30 50 10 30 50 10 30 50];
folder="HyperMatrix";
folder2 = pwd;
for x=1:12

oldfolder=cd(folder2);
HeuristicID1=heurIDrepository(HeurID1(x));
HeuristicID2=heurIDrepository(HeurID2(x));

address = char(HeuristicID1+"vs"+HeuristicID2+"_Small_pop"+num2str(Population(x))+".mat");


oldfolder=cd(folder);
hypMatrix=importdata(address);
hypMatrixCompressed=hypMatrix(:,:);
hypMatrixInverted=sort(hypMatrixCompressed.*-1);
hypMatrixInverted2=median(hypMatrixInverted);
hypMatrixInverted3(x,:)=hypMatrixInverted2(1,:);

end
for y=1:12
vector=hypMatrixInverted3(y,:);
hypMatrixInverted4(y,:)=tiedrank(vector);
end

hypMatrixInverted5(1,:)= tiedrank(cat(2,hypMatrixInverted3(1,:),hypMatrixInverted3(2,:),hypMatrixInverted3(3,:)));
hypMatrixInverted5(2,:)= tiedrank(cat(2,hypMatrixInverted3(4,:),hypMatrixInverted3(5,:),hypMatrixInverted3(6,:)));
hypMatrixInverted5(3,:)= tiedrank(cat(2,hypMatrixInverted3(7,:),hypMatrixInverted3(8,:),hypMatrixInverted3(9,:)));
hypMatrixInverted5(4,:)= tiedrank(cat(2,hypMatrixInverted3(10,:),hypMatrixInverted3(11,:),hypMatrixInverted3(12,:)));

counter=1;
for x=1:9:19
hypMatrixInverted6(:,counter)=(hypMatrixInverted4(:,x));
hypMatrixInverted6(:,counter+1)=(hypMatrixInverted4(:,x+1));
hypMatrixInverted6(:,counter+2)=(hypMatrixInverted4(:,x+2));
counter=counter+3;
end
counter=10;
for x=4:9:22
hypMatrixInverted6(:,counter)=(hypMatrixInverted4(:,x));
hypMatrixInverted6(:,counter+1)=(hypMatrixInverted4(:,x+1));
hypMatrixInverted6(:,counter+2)=(hypMatrixInverted4(:,x+2));
counter=counter+3;
end
counter=19;
for x=7:9:25
hypMatrixInverted6(:,counter)=(hypMatrixInverted4(:,x));
hypMatrixInverted6(:,counter+1)=(hypMatrixInverted4(:,x+1));
hypMatrixInverted6(:,counter+2)=(hypMatrixInverted4(:,x+2));
counter=counter+3;
end



hypMatrixInverted5 = (hypMatrixInverted5 - 82)*-1;
hypMatrixInverted6= (hypMatrixInverted6 - 28)*-1;
hypMatrixInverted4= (hypMatrixInverted4 - 28)*-1;

a=heatmap(hypMatrixInverted5);
ylabel("Heuristics")
xlabel("Configurations")

cd(folder2)
%CATEGORYNAMES = {"0.1" "0.5" "0.9" "0.1" "0.5" "0.9" "0.1" "0.5" "0.9" "0.1" "0.5" "0.9" "0.1" "0.5" "0.9" "0.1" "0.5" "0.9" "0.1" "0.5" "0.9" "0.1" "0.5" "0.9" "0.1" "0.5" "0.9" };
%violinplot(hypMatrixInverted4, CATEGORYNAMES, 'width', 0.1, 'violinalpha', 0.8, 'ShowData', false)
%boxplot(hypMatrix_concat)
%xlabel("Target Delta")
%ylabel("Quotient between obtained delta and target delta")


35 changes: 35 additions & 0 deletions Results_PreliminaryInstances.m
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folder = "HyperMatrix_Pre";
HeurID1 = 1;
HeurID2 = 2;
Population = 10;

HeuristicID1=heurIDrepository(HeurID1);
HeuristicID2=heurIDrepository(HeurID2);

address = char(HeuristicID1+"vs"+HeuristicID2+"_Small_pop"+num2str(Population)+".mat");
address2 = char(HeuristicID2+"vs"+HeuristicID1+"_Small_pop"+num2str(Population)+".mat");
folder2 = pwd;

oldfolder=cd(folder);
hypMatrix=importdata(address);
hypMatrix2=importdata(address2);
hypMatrix_T_I=(hypMatrix')*-1;
hypMatrix2_T_I=(hypMatrix2')*-1;
hypMatrix_concatenated(1,:)=hypMatrix_T_I;
hypMatrix_concatenated(2,:)=hypMatrix2_T_I;

% hypMatrix_T_I=sort(hypMatrix_T_I)
% hypMatrix2_T_I=sort(hypMatrix2_T_I)
%a=heatmap(hypMatrix_concatenated)
%
% plot(hypMatrix_T_I,'--o')
% hold on
% plot(hypMatrix2_T_I, '--o')

figure
subplot(1,2,1)
histogram(hypMatrix_T_I)
subplot(1,2,2)
histogram(hypMatrix2_T_I,'FaceColor','r')
49 changes: 49 additions & 0 deletions hypMatrixtoHeatMap_Advanced.m
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heuristicID=["LPT" "LPT" "SPT" "SPT" "MPA" "MPA" "LPA" "LPA"];
Objective=[1 2 1 2 1 2 1 2];
nbJobsV=[3];
nbMachinesV=[4];
folder="HyperMatrix_Advanced";
folder2 = pwd;
oldfolder=cd(folder);
for x=1:length(heuristicID)

if Objective(x) == 1
address =heuristicID(x) +"vsAll_"+"J"+num2str(nbJobsV(1))+"xM"+num2str(nbMachinesV(1)+".mat");
elseif Objective(x) == 2
address ="Allvs"+heuristicID(x)+"_J"+num2str(nbJobsV(1))+"xM"+num2str(nbMachinesV(1)+".mat");
end

hypMatrix=importdata(address);
hypMatrix_Inv=(hypMatrix*-1)';
hypMatrix_concat(:,x)=hypMatrix_Inv(:);
end
oldfolder=cd(folder2);
%a=heatmap(hypMatrix_concat)
CATEGORYNAMES = {"1" "2" "3" "4" "5" "6" "7" "8"};
violinplot(hypMatrix_concat,CATEGORYNAMES,'ViolinColor',[1,0,0],'width', 0.3, 'violinalpha', 0.3, 'ShowData', false)
hold on

heuristicID=["LPT" "LPT" "SPT" "SPT" "MPA" "MPA" "LPA" "LPA"];
Objective=[1 2 1 2 1 2 1 2];
nbJobsV=[3];
nbMachinesV=[4];
folder="HyperMatrix_Advanced2";
oldfolder=cd(folder2);
oldfolder=cd(folder);
for x=1:length(heuristicID)

if Objective(x) == 1
address =heuristicID(x) +"vsAll_"+"J"+num2str(nbJobsV(1))+"xM"+num2str(nbMachinesV(1)+".mat");
elseif Objective(x) == 2
address ="Allvs"+heuristicID(x)+"_J"+num2str(nbJobsV(1))+"xM"+num2str(nbMachinesV(1)+".mat");
end

hypMatrix=importdata(address);
hypMatrix_Inv=(hypMatrix*-1)';
hypMatrix_concat(:,x)=hypMatrix_Inv(:);
end
oldfolder=cd(folder2);
%a=heatmap(hypMatrix_concat)
CATEGORYNAMES = {"1" "2" "3" "4" "5" "6" "7" "8"};
violinplot(hypMatrix_concat, CATEGORYNAMES, 'ViolinColor',[0,0,1],'width', 0.3, 'violinalpha', 0.3, 'ShowData', false)
% hist(hypMatrix_concat(1,:))
60 changes: 60 additions & 0 deletions hypMatrixtoViolin_Advanced.m
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function []= hypMatrixtoViolin_Advanced(folder, HeurID, objective)
global hypMatrix_concat

nbJobsV = [3];
nbMachinesV = [4];
heuristicID=heurIDrepository(HeurID);
heurIDV=HeurIDVector(HeurID);

if objective == 1
address =heuristicID(1) +"vsAll_"+"J"+num2str(nbJobsV(1))+"xM"+num2str(nbMachinesV(1));
elseif objective == 2
address ="Allvs"+heuristicID(1)+"_J"+num2str(nbJobsV(1))+"xM"+num2str(nbMachinesV(1));
end

folder2 = pwd;
oldfolder=cd(folder);
oldfolder=cd(address);

for x=10:10:50
delta_code = "_Delta_"+num2str(x);
address2= address+delta_code+".mat";
hypMatrix=importdata(address2);
HeurID_makespan_matrix = hypMatrix(:,HeurID+2);
if objective == 1
for r=1:50
RemVector_makespan_matrix(r,1) = min([hypMatrix(r,heurIDV(1)+2) hypMatrix(r,heurIDV(2)+2) hypMatrix(r,heurIDV(3)+2)]);
end
Matrix1 = HeurID_makespan_matrix./RemVector_makespan_matrix;
Matrix2 = (RemVector_makespan_matrix-HeurID_makespan_matrix)/x;
elseif objective == 2
for r=1:50
RemVector_makespan_matrix(r,1) = max([hypMatrix(r,heurIDV(1)+2) hypMatrix(r,heurIDV(2)+2) hypMatrix(r,heurIDV(3)+2)]);
end
Matrix1 =RemVector_makespan_matrix./HeurID_makespan_matrix;
Matrix2 = (HeurID_makespan_matrix-RemVector_makespan_matrix)/x;
end


y=x/10;
hypMatrix_concat(:,y)= Matrix2(:,1);
end
disp("Mean")
hypMatrix_mean= mean(hypMatrix_concat)
disp("Median")
hypMatrix_median=median(hypMatrix_concat)

cd(folder2)
CATEGORYNAMES = {"10" "20" "30" "40" "50"};
violinplot(hypMatrix_concat, CATEGORYNAMES,'ViolinColor',[0,0,1],'width', 0.3, 'violinalpha', 0.3, 'ShowData', false)


%boxplot(hypMatrix_concat)
xlabel("Target Delta")
ylabel("Quotient between obtained delta and target delta")

end




7 changes: 7 additions & 0 deletions makespan.m
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function [makespan] = makespan(instance, heurID)

instance1 = createJSSPInstanceFromInstance(instance);

makespan = JSSPSolveInstance(instance1, heurID);

end

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