b0351ae298
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@157 331e1502-861f-0410-8da2-ba01fb791d7f
103 lines
5 KiB
TeX
103 lines
5 KiB
TeX
\section{moeo\-IBEASorting$<$ EOT, Fitness $>$ Class Template Reference}
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\label{classmoeoIBEASorting}\index{moeoIBEASorting@{moeoIBEASorting}}
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Functor The sorting phase of IBEA (Indicator-Based Evolutionary Algorithm) without uncertainty Adapted from the Zitzler and K\~{A}¼nzli paper \char`\"{}Indicator-Based Selection in Multiobjective Search\char`\"{} (2004) Of course, Fitness needs to be an {\bf eo\-Pareto\-Fitness} object.
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{\tt \#include $<$moeo\-IBEA.h$>$}
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Inheritance diagram for moeo\-IBEASorting$<$ EOT, Fitness $>$::\begin{figure}[H]
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\begin{center}
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\leavevmode
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\includegraphics[height=6cm]{classmoeoIBEASorting}
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\end{center}
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\end{figure}
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\subsection*{Public Member Functions}
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\begin{CompactItemize}
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\item
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{\bf moeo\-IBEASorting} ({\bf moeo\-Binary\-Quality\-Indicator}$<$ Fitness $>$ $\ast$\_\-I, const double \_\-kappa)
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\begin{CompactList}\small\item\em constructor \item\end{CompactList}\end{CompactItemize}
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\subsection*{Private Member Functions}
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\begin{CompactItemize}
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\item
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void {\bf set\-Bounds} (const {\bf eo\-Pop}$<$ EOT $>$ \&\_\-pop)
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\begin{CompactList}\small\item\em computation and setting of the bounds for each objective \item\end{CompactList}\item
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void {\bf fitnesses} (const {\bf eo\-Pop}$<$ EOT $>$ \&\_\-pop)
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\begin{CompactList}\small\item\em computation and setting of the fitness for each individual of the population \item\end{CompactList}\end{CompactItemize}
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\subsection*{Private Attributes}
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\begin{CompactItemize}
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\item
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double {\bf kappa}\label{classmoeoIBEASorting_4789daab5ea5e215075d7430f343a321}
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\begin{CompactList}\small\item\em scaling factor kappa \item\end{CompactList}\end{CompactItemize}
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\subsection{Detailed Description}
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\subsubsection*{template$<$class EOT, class Fitness = typename EOT::Fitness$>$ class moeo\-IBEASorting$<$ EOT, Fitness $>$}
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Functor The sorting phase of IBEA (Indicator-Based Evolutionary Algorithm) without uncertainty Adapted from the Zitzler and K\~{A}¼nzli paper \char`\"{}Indicator-Based Selection in Multiobjective Search\char`\"{} (2004) Of course, Fitness needs to be an {\bf eo\-Pareto\-Fitness} object.
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Definition at line 84 of file moeo\-IBEA.h.
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\subsection{Constructor \& Destructor Documentation}
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\index{moeoIBEASorting@{moeo\-IBEASorting}!moeoIBEASorting@{moeoIBEASorting}}
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\index{moeoIBEASorting@{moeoIBEASorting}!moeoIBEASorting@{moeo\-IBEASorting}}
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\subsubsection{\setlength{\rightskip}{0pt plus 5cm}template$<$class EOT, class Fitness = typename EOT::Fitness$>$ {\bf moeo\-IBEASorting}$<$ EOT, Fitness $>$::{\bf moeo\-IBEASorting} ({\bf moeo\-Binary\-Quality\-Indicator}$<$ Fitness $>$ $\ast$ {\em \_\-I}, const double {\em \_\-kappa})\hspace{0.3cm}{\tt [inline]}}\label{classmoeoIBEASorting_4d00a499f4d03b8cf66e9ce8f68cb174}
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constructor
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\begin{Desc}
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\item[Parameters:]
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\begin{description}
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\item[{\em eo\-Binary\-Quality\-Indicator$<$EOT$>$$\ast$}]\_\-I the binary quality indicator to use in the selection process \item[{\em double}]\_\-kappa scaling factor kappa \end{description}
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\end{Desc}
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Definition at line 96 of file moeo\-IBEA.h.
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References moeo\-IBEASorting$<$ EOT, Fitness $>$::kappa.
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\subsection{Member Function Documentation}
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\index{moeoIBEASorting@{moeo\-IBEASorting}!setBounds@{setBounds}}
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\index{setBounds@{setBounds}!moeoIBEASorting@{moeo\-IBEASorting}}
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\subsubsection{\setlength{\rightskip}{0pt plus 5cm}template$<$class EOT, class Fitness = typename EOT::Fitness$>$ void {\bf moeo\-IBEASorting}$<$ EOT, Fitness $>$::set\-Bounds (const {\bf eo\-Pop}$<$ EOT $>$ \& {\em \_\-pop})\hspace{0.3cm}{\tt [inline, private, virtual]}}\label{classmoeoIBEASorting_f29f38584c69217f25e904118f6bfb2b}
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computation and setting of the bounds for each objective
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\begin{Desc}
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\item[Parameters:]
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\begin{description}
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\item[{\em const}]eo\-Pop$<$EOT$>$\& \_\-pop the population \end{description}
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\end{Desc}
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Implements {\bf moeo\-IBEA$<$ EOT, Fitness $>$} \doxyref{}{p.}{classmoeoIBEA}.
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Definition at line 121 of file moeo\-IBEA.h.
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References moeo\-IBEA$<$ EOT, Fitness $>$::I, and moeo\-Binary\-Quality\-Indicator$<$ EOFitness $>$::set\-Bounds().\index{moeoIBEASorting@{moeo\-IBEASorting}!fitnesses@{fitnesses}}
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\index{fitnesses@{fitnesses}!moeoIBEASorting@{moeo\-IBEASorting}}
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\subsubsection{\setlength{\rightskip}{0pt plus 5cm}template$<$class EOT, class Fitness = typename EOT::Fitness$>$ void {\bf moeo\-IBEASorting}$<$ EOT, Fitness $>$::fitnesses (const {\bf eo\-Pop}$<$ EOT $>$ \& {\em \_\-pop})\hspace{0.3cm}{\tt [inline, private, virtual]}}\label{classmoeoIBEASorting_63c3953d362b41e875e6e7759a308e07}
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computation and setting of the fitness for each individual of the population
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\begin{Desc}
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\item[Parameters:]
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\begin{description}
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\item[{\em const}]eo\-Pop$<$EOT$>$\& \_\-pop the population \end{description}
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\end{Desc}
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Implements {\bf moeo\-IBEA$<$ EOT, Fitness $>$} \doxyref{}{p.}{classmoeoIBEA}.
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Definition at line 150 of file moeo\-IBEA.h.
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References moeo\-IBEASorting$<$ EOT, Fitness $>$::kappa, and eo\-Value\-Param$<$ std::vector$<$ Worth\-T $>$ $>$::value().
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The documentation for this class was generated from the following file:\begin{CompactItemize}
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\item
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moeo\-IBEA.h\end{CompactItemize}
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