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<title>function f = initialize_variables(N,problem)</title>
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<h1>function f = initialize_variables(N,problem)</h1><pre class="codeinput"><span class="comment">% function f = initialize_variables(N,problem)</span>
<span class="comment">% N - Population size</span>
<span class="comment">% problem - takes integer values 1 and 2 where,</span>
<span class="comment">% '1' for MOP1</span>
<span class="comment">% '2' for MOP2</span>
<span class="comment">%</span>
<span class="comment">% This function initializes the population with N individuals and each</span>
<span class="comment">% individual having M decision variables based on the selected problem.</span>
<span class="comment">% M = 6 for problem MOP1 and M = 12 for problem MOP2. The objective space</span>
<span class="comment">% for MOP1 is 2 dimensional while for MOP2 is 3 dimensional.</span>
<span class="comment">% Both the MOP's has 0 to 1 as its range for all the decision variables.</span>
min = 0;
max = 1;
<span class="keyword">switch</span> problem
<span class="keyword">case</span> 1
M = 6;
K = 8;
<span class="keyword">case</span> 2
M = 12;
K = 15;
<span class="keyword">end</span>
<span class="keyword">for</span> i = 1 : N
<span class="comment">% Initialize the decision variables</span>
<span class="keyword">for</span> j = 1 : M
f(i,j) = rand(1); <span class="comment">% i.e f(i,j) = min + (max - min)*rand(1);</span>
<span class="keyword">end</span>
<span class="comment">% Evaluate the objective function</span>
f(i,M + 1: K) = evaluate_objective(f(i,:),problem);
<span class="keyword">end</span>
</pre<p class="footer"><br>
Published with MATLAB® 7.0<br></p>
<!--
##### SOURCE BEGIN #####
%% 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
##### SOURCE END #####
-->
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