Contents

function f = initialize_variables(N, M, V, min_tange, max_range)

This function initializes the chromosomes. Each chromosome has the following at this stage * set of decision variables * objective function values

where, N - Population size M - Number of objective functions V - Number of decision variables min_range - A vector of decimal values which indicate the minimum value for each decision variable. max_range - Vector of maximum possible values for decision variables.

min = min_range;
max = max_range;

% K is the total number of array elements. For ease of computation decision
% variables and objective functions are concatenated to form a single
% array. For crossover and mutation only the decision variables are used
% while for selection, only the objective variable are utilized.

K = M + V;

Initialize each chromosome

For each chromosome perform the following (N is the population size)

for i = 1 : N
    % Initialize the decision variables based on the minimum and maximum
    % possible values. V is the number of decision variable. A random
    % number is picked between the minimum and maximum possible values for
    % the each decision variable.
    for j = 1 : V
        f(i,j) = min(j) + (max(j) - min(j))*rand(1);
    end
    % For ease of computation and handling data the chromosome also has the
    % vlaue of the objective function concatenated at the end. The elements
    % V + 1 to K has the objective function valued.
    % The function evaluate_objective takes one chromosome at a time,
    % infact only the decision variables are passed to the function along
    % with information about the number of objective functions which are
    % processed and returns the value for the objective functions. These
    % values are now stored at the end of the chromosome itself.
    f(i,V + 1: K) = evaluate_objective(f(i,:), M, V);
end