DEPMS.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

%% DE Parameters
MaxIt = 100;      % Maximum Number of Iterations
nPop = 20;        % Population Size

beta_min = 0.2;   % Lower Bound of Scaling Factor
beta_max = 0.8;   % Upper Bound of Scaling Factor
pCR = 0.2;        % Crossover Probability

%% Initialization
tic
empty_individual.Position = [];
empty_individual.Cost = [];
empty_individual.Sol = [];

BestSol.Cost = inf;
pop = repmat(empty_individual, nPop, 1);
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
BestCost = zeros(MaxIt, 1);

%% DE
for it = 1:MaxIt
for i = 1:nPop
x = pop(i).Position;
A = randperm(nPop);
A(A == i) = [];
a = A(1);
b = A(2);
c = A(3);
% Mutation
%beta = unifrnd(beta_min, beta_max);
beta = unifrnd(beta_min, beta_max, VarSize);
y = pop(a).Position+beta.*(pop(b).Position-pop(c).Position);
y = max(y, VarMin);
y = min(y, VarMax);
% Crossover
z = zeros(size(x));
j0 = randi([1 numel(x)]);
for j = 1:numel(x)
if j == j0 || rand <= pCR
z(j) = y(j);
else
z(j) = x(j);
end
end
NewSol.Position = z;
[NewSol.Cost NewSol.Sol] = CostFunction(NewSol.Position);
if NewSol.Cost<pop(i).Cost
pop(i) = NewSol;
if pop(i).Cost<BestSol.Cost
BestSol = pop(i);
end
end
end
% Update Best Cost
BestCost(it) = BestSol.Cost;
% Show Iteration Information
% Store NFE
nfe(it)=NFE;
disp(['Iteration ' num2str(it) ': Best Cost = ' 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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