initialize_variables.m

多目标优化进化算法目前公认效果收敛性最好的算法NSGA2源码

function f = initialize_variables(N,problem)

% function f = initialize_variables(N,problem)
% N - Population size
% problem - takes integer values 1 and 2 where,
%           '1' for MOP1
%           '2' for MOP2
%
% This function initializes the population with N individuals and each
% individual having M decision variables based on the selected problem. 
% M = 6 for problem MOP1 and M = 12 for problem MOP2. The objective space
% for MOP1 is 2 dimensional while for MOP2 is 3 dimensional.

% Both the MOP's has 0 to 1 as its range for all the decision variables. 
min = 0;
max = 1;
switch problem
    case 1
        M = 6;
        K = 8;
    case 2
        M = 12;
        K = 15;
end
for i = 1 : N
    % Initialize the decision variables
    for j = 1 : M
        f(i,j) = rand(1); % i.e f(i,j) = min + (max - min)*rand(1);
    end
    % Evaluate the objective function
    f(i,M + 1: K) = evaluate_objective(f(i,:),problem);
end