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@@ -276,38 +276,51 @@ rates for fully random search with 400 iterations.
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\begin{figure}
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\begin{mdframed}
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- \label{rand_flow}
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\includegraphics[scale=0.4]{crossover_flow.pdf}
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\caption{Flowchart of the crossover algorithm.}
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+ \label{cross_flow}
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\end{mdframed}
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\end{figure}
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+\subsubsection{Dependence on the parameter p}
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+First experiments were made to select the value for the crossover parameter
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+p. Results are compiled in graphs~\ref{res_gen2},~\ref{res_gen2z},\ref{res_gen3}
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+and~\ref{res_gen4}.
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+Graph~\ref{res_gen2}, represents the results obtained
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+in dimension 2 between 10 and 500 points. The curve obtained is, with no
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+surprise again,
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+the characteristic curve of the average evolution of the discrepancy we already
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+saw with the previous experiments.
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+The most interesting part of these results are concentrated --- once again ---
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+between 80 and 160 points were the different curves splits.
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+The graph~\ref{res_gen2z} is a zoom of~\ref{res_gen2} in this window, and
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+graphs~\ref{res_gen3} and~\ref{res_gen4} are focused directly into it too.
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+
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\begin{figure}
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- \label{rand_flow}
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\includegraphics[scale=0.3]{Results/res_gen_2.png}
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-\caption{Dependence on iterations number: D=3}
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+\caption{Dependence on parameter p: D=2}
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+ \label{res_gen2}
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\end{figure}
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\begin{figure}
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- \label{rand_flow}
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\includegraphics[scale=0.3]{Results/res_gen_2_zoom.png}
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-\caption{Dependence on iterations number: D=3}
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+\caption{Dependence on parameter p (zoom): D=2}
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+\label{res_gen2z}
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\end{figure}
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\begin{figure}
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- \label{rand_flow}
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\includegraphics[scale=0.3]{Results/res_gen_3_zoom.png}
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-\caption{Dependence on iterations number: D=3}
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+\caption{Dependence on parameter p: D=3}
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+ \label{res_gen3}
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\end{figure}
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\begin{figure}
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- \label{rand_flow}
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\includegraphics[scale=0.3]{Results/res_gen_4_zoom.png}
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-\caption{Dependence on iterations number: D=3}
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+\caption{Dependence on parameter p: D=4}
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+ \label{res_gen4}
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\end{figure}
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-As prev we investigated the stability
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-of the algorithm with regards to the number of iterations. We present here
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-the result in dimension 3 in the graph~\ref{iter_sa}. Once again we
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+Once again we investigated the stability
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+of the algorithm with regards to the number of iterations. Once again we
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restricted the window between 80 and 180 points were curves are split.
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An interesting phenomena can be observed: the error rates are somehow
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invariant w.r.t.\ the number of iteration and once again the 1000 iterations
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