TLBOPMS.m

clc;
clear;
close all;
global NFE;
NFE=0;

%% Problem 
I=20; % Tasks
J=6; % Machines
Pmin=10; % Process time  min
Pmax=50; % Process time max
Smin=3; % Setup time min
Smax=9; % Setup time max
model=CreateModel(I,J,Pmin,Pmax,Smin,Smax);        % Create Model of the Problem

CostFunction=@(x) MyCost(x,model);       % Cost Function
nVar=model.nVar;        % Number of Decision Variables
VarSize=[1 nVar];       % Size of Decision Variables Matrix
VarMin = 0;          % Lower Bound of Decision Variables
VarMax = 1;          % Upper Bound of Decision Variables

%% TLBO Parameters
MaxIt = 100;         % Maximum Number of Iterations
nPop = 20;           % Population Size
tic
%% Start 
% Empty Individuals
empty_individual.Position = [];
empty_individual.Cost = [];
empty_individual.Sol = [];

% Population Array
pop = repmat(empty_individual, nPop, 1);
% Initialize Best Solution
BestSol.Cost = inf;
% Population Members
for i = 1:nPop
pop(i).Position = unifrnd(VarMin, VarMax, VarSize);
[pop(i).Cost pop(i).Sol] = CostFunction(pop(i).Position);
if pop(i).Cost < BestSol.Cost
BestSol = pop(i);
end
end
% Best Cost Record
BestCost = zeros(MaxIt, 1);

%% TLBO 
for it = 1:MaxIt
% Calculate Population Mean
Mean = 0;
for i = 1:nPop
Mean = Mean + pop(i).Position;
end
Mean = Mean/nPop;
% Select Teacher
Teacher = pop(1);
for i = 2:nPop
if pop(i).Cost < Teacher.Cost
Teacher = pop(i);
end
end

% Teacher Phase
for i = 1:nPop
% Create Empty Solution
newsol = empty_individual;
% Teaching Factor
TF = randi([1 2]);
% Teaching (moving towards teacher)
newsol.Position = pop(i).Position ...
+ rand(VarSize).*(Teacher.Position - TF*Mean);
% Clipping
newsol.Position = max(newsol.Position, VarMin);
newsol.Position = min(newsol.Position, VarMax);
% Evaluation
[newsol.Cost newsol.Sol] = CostFunction(newsol.Position);
% Comparision
if newsol.Cost<pop(i).Cost
pop(i) = newsol;
if pop(i).Cost < BestSol.Cost
BestSol = pop(i);
end
end
end

% Learner Phase
for i = 1:nPop
A = 1:nPop;
A(i) = [];
j = A(randi(nPop-1));
Step = pop(i).Position - pop(j).Position;
if pop(j).Cost < pop(i).Cost
Step = -Step;
end
% Create Empty Solution
newsol = empty_individual;
% Teaching (moving towards teacher)
newsol.Position = pop(i).Position + rand(VarSize).*Step;
% Clipping
newsol.Position = max(newsol.Position, VarMin);
newsol.Position = min(newsol.Position, VarMax);
% Evaluation
[newsol.Cost newsol.Sol] = CostFunction(newsol.Position);
% Comparision
if newsol.Cost<pop(i).Cost
pop(i) = newsol;
if pop(i).Cost < BestSol.Cost
BestSol = pop(i);
end
end
end
BestCost(it) = BestSol.Cost;
% Iteration 
disp(['In ITR ' num2str(it) ': TLBO Cost Value Is = ' num2str(BestCost(it))]);

% Plot Res
figure(1);
PlotSolution(BestSol.Sol,model);

end

%% Show Results
% figure(1);
% PlotSolution(BestSol.Sol,model);

figure;
plot(BestCost,'k','LineWidth',2);
xlabel('Iteration');
ylabel('Best Cost');
ax = gca; 
ax.FontSize = 12; 
ax.FontWeight='bold';
grid on;
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