?? tournament_selection.html
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<title>function f = selection_individuals(chromosome,pool_size,tour_size)</title>
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<h1>function f = selection_individuals(chromosome,pool_size,tour_size)</h1><pre class="codeinput"><span class="comment">% function selection_individuals(chromosome,pool_size,tour_size) is the</span>
<span class="comment">% selection policy for selecting the individuals for the mating pool. The</span>
<span class="comment">% selection is based on tournament selection. Argument 'chromosome' is the</span>
<span class="comment">% current generation population from which the individuals are selected to</span>
<span class="comment">% form a mating pool of size 'pool_size' after performing tournament</span>
<span class="comment">% selection, with size of the tournament being 'tour_size'. By varying the</span>
<span class="comment">% tournament size the selection pressure can be adjusted.</span>
[pop,variables] = size(chromosome);
rank = variables - 1;
distance = variables;
<span class="keyword">for</span> i = 1 : pool_size
<span class="keyword">for</span> j = 1 : tour_size
candidate(j) = round(pop*rand(1));
<span class="keyword">if</span> candidate(j) == 0
candidate(j) = 1;
<span class="keyword">end</span>
<span class="keyword">if</span> j > 1
<span class="keyword">while</span> ~isempty(find(candidate(1 : j - 1) == candidate(j)))
candidate(j) = round(pop*rand(1));
<span class="keyword">if</span> candidate(j) == 0
candidate(j) = 1;
<span class="keyword">end</span>
<span class="keyword">end</span>
<span class="keyword">end</span>
<span class="keyword">end</span>
<span class="keyword">for</span> j = 1 : tour_size
c_obj_rank(j) = chromosome(candidate(j),rank);
c_obj_distance(j) = chromosome(candidate(j),distance);
<span class="keyword">end</span>
min_candidate = <span class="keyword">...</span>
find(c_obj_rank == min(c_obj_rank));
<span class="keyword">if</span> length(min_candidate) ~= 1
max_candidate = <span class="keyword">...</span>
find(c_obj_distance(min_candidate) == max(c_obj_distance(min_candidate)));
<span class="keyword">if</span> length(max_candidate) ~= 1
max_candidate = max_candidate(1);
<span class="keyword">end</span>
f(i,:) = chromosome(candidate(min_candidate(max_candidate)),:);
<span class="keyword">else</span>
f(i,:) = chromosome(candidate(min_candidate(1)),:);
<span class="keyword">end</span>
<span class="keyword">end</span>
</pre><p class="footer"><br>
Published with MATLAB® 7.0<br></p>
<!--
##### SOURCE BEGIN #####
%% function f = selection_individuals(chromosome,pool_size,tour_size)
% function selection_individuals(chromosome,pool_size,tour_size) is the
% selection policy for selecting the individuals for the mating pool. The
% selection is based on tournament selection. Argument 'chromosome' is the
% current generation population from which the individuals are selected to
% form a mating pool of size 'pool_size' after performing tournament
% selection, with size of the tournament being 'tour_size'. By varying the
% tournament size the selection pressure can be adjusted.
[pop,variables] = size(chromosome);
rank = variables - 1;
distance = variables;
for i = 1 : pool_size
for j = 1 : tour_size
candidate(j) = round(pop*rand(1));
if candidate(j) == 0
candidate(j) = 1;
end
if j > 1
while ~isempty(find(candidate(1 : j - 1) == candidate(j)))
candidate(j) = round(pop*rand(1));
if candidate(j) == 0
candidate(j) = 1;
end
end
end
end
for j = 1 : tour_size
c_obj_rank(j) = chromosome(candidate(j),rank);
c_obj_distance(j) = chromosome(candidate(j),distance);
end
min_candidate = ...
find(c_obj_rank == min(c_obj_rank));
if length(min_candidate) ~= 1
max_candidate = ...
find(c_obj_distance(min_candidate) == max(c_obj_distance(min_candidate)));
if length(max_candidate) ~= 1
max_candidate = max_candidate(1);
end
f(i,:) = chromosome(candidate(min_candidate(max_candidate)),:);
else
f(i,:) = chromosome(candidate(min_candidate(1)),:);
end
end
##### SOURCE END #####
-->
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