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发表于 30-11-2010 04:46 PM
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回复 1# yeongchuan88
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
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