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\textbf{ParadisEO Practices}  {\copyright Franck Seynhaeve,
Jean-Charles Boisson, Thomas Legrand} \Large{\textbf{\\\\
Lesson 5: Implement a genetic algorithm using ParadisEO}}

\normalsize

 \vspace{-0,3cm}

\section{Example}

    The archive {\tt paradiseo\_practices\_0208.tgz} installed
    on your computer contains a genetic algorithm implemented using ParadisEO-EO~
    (see {\tt gen\_algo} in the {\bf build/lesson5} directory).

    \medskip
    To run it, please go in {\bf build/lesson5} and start the program {\tt gen\_algo} by giving
    one of the TSP instances located in {\bf tsp/benchs}.

    \medskip
    When entering {\tt ./gen\_algo ../../tsp/benchs/berlin52.tsp}, you should end up with the
    following outputs:

    \smallskip
    \noindent
    \texttt{>> Loading [../tsp/benchs/berlin52.tsp]}\\
    \texttt{[From] -26461  52 39 12 29 44 2 26 13 40 7 35 14 28 25 41 6 51 10 50 45 19 0 38 15}\\
    \texttt{33 42 21 18 32 37 9 5 20 34 43 16 30 1 23 22 4 27 36 4946 47 48 11 17 8 31 24 3}\\
    \texttt{STOP in eoGenContinue: Reached maximum number of generations [1000/1000]}\\
    \texttt{[To] -13068  52 45 24 28 22 19 21 30 17 31 36 46 25 13 12 26 27 51 10 14 37 23 4 15 49}\\
    \texttt{20 2 8 42 50 11 47 39 38 35 34 44 18 40 9 7 32 3 5 33 16 41 6 1 29 0 48
    43} \\

    \medskip

    The printed-out results show for the initial best solution and the final one~:
    \\ \hspace*{1cm}-the length of the route
    \\ \hspace*{1cm}-the number of cities
    \\ \hspace*{1cm}-the route itself (notice that the city index starts from 0).


\section{Study the genetic algorithm dedicated components}

    Study the {\tt gen\_algo.cpp} file located in the {\bf lesson5} directory
    using~:
    \begin{itemize}
       \item[$\bullet$] the ParadisEO-EO API documentation available at~:

       \hspace{1cm}http$\,:$//eodev.sourceforge.net/eo/doc/html/index.html

       \item[$\bullet$] the source files located in the {\bf tsp/src/} directory
    \end{itemize}


\section{Customize the GA}

    Make a backup (copy) of the cpp file {\tt gen\_algo.cpp}. You can now modify the
    original {\tt gen\_algo.cpp} and use the existing makefiles to compile it.

    Edit and modify the {\tt gen\_algo.cpp} file~:
    \begin{itemize}
       \item[$\bullet$] Try to tune a few parameters of the GA
       (selection criteria, stopping criteria ...).
       \item[$\bullet$] Then, try to change the initialization of the population
       by applying one of the local searches on each individual.
    \end{itemize}

    \smallskip
    To compile {\tt gen\_algo.cpp},you should use the
    command {\tt make} from {\bf build/lesson5}.

    \medskip
    Finally, test your modifications on several TSP instances ({\tt berlin52},
    {\tt eil101} ...) and compare the results you get.

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