% Phase 3: Determination of the risk coefficient value using TOPSIS


% Step1: Creating the decision matrix (9 hazards, 7 risk parameters)
X = [
    0.0791	0.1827	0.0865	0.0798	0.0868	0.1622	0.1493;
0.1438	0.0490	0.1561	0.0533	0.0644	0.1096	0.1276;
0.1678	0.0286	0.1831	0.1572	0.1135	0.1427	0.0733;
0.2059	0.1824	0.2007	0.1686	0.1858	0.0922	0.1562;
0.1829	0.1157	0.1183	0.1642	0.1819	0.0758	0.0763;
0.0402	0.0653	0.0542	0.1359	0.1064	0.0572	0.0421;
0.0816	0.0586	0.1117	0.1171	0.1536	0.0102	0.0619;
0.0589	0.1427	0.0430	0.0831	0.0836	0.1310	0.1395;
0.0398	0.1751	0.0463	0.0408	0.0240	0.2192	0.1737;
];

% Risk Parameter Weights
weights = [0.1445, 0.0481, 0.1195, 0.1762, 0.1558, 0.1573, 0.1987];

% Determining cost and benefit criteria
% 1 = Benefit, -1 = Cost
criteria_type = [1, 1, 1, -1, 1, 1, -1];

% Step 2: Creation of the weighted decision matrix
V = zeros(size(X));
for j = 1:size(X, 2)
    V(:,j) = X(:,j) * weights(j);
end

% Step 3: Positive and negative ideal solutions values 
V_max = zeros(1, size(X, 2)); % Positive ideal solutions values
V_min = zeros(1, size(X, 2)); % Negative ideal solutions values
for j = 1:size(X, 2)
    if criteria_type(j) == 1 % Benefit criteria
        V_max(j) = max(V(:,j));
        V_min(j) = min(V(:,j));
    else % Cost criteria
        V_max(j) = min(V(:,j));
        V_min(j) = max(V(:,j));
    end
end

% Step 4: Determined of positive and negative distance values 
S_max = zeros(size(X, 1), 1);
S_min= zeros(size(X, 1), 1);
for i = 1:size(X, 1)
    S_max(i) = sqrt(sum((V(i,:) - V_max).^2));
    S_min(i) = sqrt(sum((V(i,:) - V_min).^2));
end

% Step 5: Calculate of closeness coefficient
C = S_min ./ (S_max + S_min);

% Normalization of closeness coefficient
C_total = sum(C);
C_normalized = C / C_total;

% Step 6: Ranking  of hazards
[~, rank_indices] = sort(C_normalized, 'descend');
disp('Normalized closeness coefficient values (C) and rankings of hazards:');
for i = 1:size(X, 1)
    fprintf('Hazard %d: C = %.4f, Normalized C = %.4f, Rank: %d\n', i, C(i), C_normalized(i), find(rank_indices == i));
end
disp('Ranked Hazards:');
disp(rank_indices');