Price=[1 4 2;0.25 1 0.5;0.5 2 1]
Features=[1 1/6 0.5;6 1 4;2 0.25 1]
Memory=[1 1/9 0.5;9 1 4;2 0.25 1]
Criteria=[1 3 5;1/3 1 2;0.2 0.5 1]

%a) and b)
%Calculation of local priority vectors and consistency indices

%For each variable:

%1. solve eigenvectors and eigenvalues:
[v, l]=eig(Price);
%2. Discover largest eigenvalue and the corresponding eigenvector:
[eig_max, ind]=max(diag(l));
%3. calculate local priority vector:
w=v(:,ind);
w_Price=w/sum(w)
%4. calculate consistency index:
CI_Price=(eig_max-3)/2
%5. calculate consistency ratio:
CR_Price=CI_Price/0.58

%1. solve eigenvectors and eigenvalues:
[v, l]=eig(Features);
%2. Discover largest eigenvalue and the corresponding eigenvector:
[eig_max, ind]=max(diag(l));
%3. calculate local priority vector:
w=v(:,ind);
w_Features=w/sum(w)
%4. calculate consistency index:
CI_Features=(eig_max-3)/2
%5. calculate consistency ratio:
CR_Features=CI_Features/0.58

%1. solve eigenvectors and eigenvalues:
[v, l]=eig(Memory);
%2. Discover largest eigenvalue and the corresponding eigenvector:
[eig_max, ind]=max(diag(l));
%3. calculate local priority vector:
w=v(:,ind);
w_Memory=w/sum(w)
%4. calculate consistency index:
CI_Memory=(eig_max-3)/2
%5. calculate consistency ratio:
CR_Memory=CI_Memory/0.58

%1. solve eigenvectors and eigenvalues:
[v, l]=eig(Criteria);
%2. Discover largest eigenvalue and the corresponding eigenvector:
[eig_max, ind]=max(diag(l));
%3. calculate local priority vector:
w=v(:,ind);
w_Criteria=w/sum(w)
%4. calculate consistency index:
CI_Criteria=(eig_max-3)/2
%5. calculate consistency ratio:
CR_Criteria=CI_Criteria/0.58

%c)
%Calculation of total priorities:
Tot_priors=[w_Price w_Features w_Memory]*w_Criteria

%d) 
%Repetition of calculations with replica of A added to the set of alternatives
Price=[Price Price(:,1)];
Price=[Price;Price(1,:)];
Features=[Features Features(:,1)];
Features=[Features;Features(1,:)];
Memory=[Memory Memory(:,1)];
Memory=[Memory;Memory(1,:)];

%1. solve eigenvectors and eigenvalues:
[v l]=eig(Price);
%2. Discover largest eigenvalue and the corresponding eigenvector:
[eig_max ind]=max(diag(l));
%3. calculate local priority vector:
w=v(:,ind);
w_Price=w/sum(w)
%4. calculate consistency index:
CI_Price=(eig_max-4)/3
%5. calculate consistency ratio:
CR_Price=CI_Price/0.9

%1. solve eigenvectors and eigenvalues:
[v l]=eig(Features);
%2. Discover largest eigenvalue and the corresponding eigenvector:
[eig_max ind]=max(diag(l));
%3. calculate local priority vector:
w=v(:,ind);
w_Features=w/sum(w)
%4. calculate consistency index:
CI_Features=(eig_max-4)/3
%5. calculate consistency ratio:
CR_Features=CI_Features/0.9

%1. solve eigenvectors and eigenvalues:
[v l]=eig(Memory);
%2. Discover largest eigenvalue and the corresponding eigenvector:
[eig_max ind]=max(diag(l));
%3. calculate local priority vector:
w=v(:,ind);
w_Memory=w/sum(w)
%4. calculate consistency index:
CI_Memory=(eig_max-4)/3
%5. calculate consistency ratio:
CR_Memory=CI_Memory/0.9

%Calculation of total priorities:
Tot_priors=[w_Price w_Features w_Memory]*w_Criteria