\section{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment$<$ MOEOT $>$ Class Template Reference}
\label{classmoeoFastNonDominatedSortingFitnessAssignment}\index{moeoFastNonDominatedSortingFitnessAssignment@{moeoFastNonDominatedSortingFitnessAssignment}}
Fitness assignment sheme based on Pareto-dominance count proposed in: N.  


{\tt \#include $<$moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment.h$>$}

Inheritance diagram for moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment$<$ MOEOT $>$::\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[height=5cm]{classmoeoFastNonDominatedSortingFitnessAssignment}
\end{center}
\end{figure}
\subsection*{Public Types}
\begin{CompactItemize}
\item 
typedef MOEOT::Objective\-Vector {\bf Objective\-Vector}\label{classmoeoFastNonDominatedSortingFitnessAssignment_7bca09c8cf084700172a6e0dfcf6c381}

\begin{CompactList}\small\item\em the objective vector type of the solutions \item\end{CompactList}\end{CompactItemize}
\subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
{\bf moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment} ()\label{classmoeoFastNonDominatedSortingFitnessAssignment_d02bd6ca60399f6171c08fa42f131644}

\begin{CompactList}\small\item\em Default ctor. \item\end{CompactList}\item 
{\bf moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment} ({\bf moeo\-Objective\-Vector\-Comparator}$<$ {\bf Objective\-Vector} $>$ \&\_\-comparator)
\begin{CompactList}\small\item\em Ctor where you can choose your own way to compare objective vectors. \item\end{CompactList}\item 
void {\bf operator()} ({\bf eo\-Pop}$<$ MOEOT $>$ \&\_\-pop)
\begin{CompactList}\small\item\em Sets the fitness values for every solution contained in the population \_\-pop. \item\end{CompactList}\item 
void {\bf update\-By\-Deleting} ({\bf eo\-Pop}$<$ MOEOT $>$ \&\_\-pop, {\bf Objective\-Vector} \&\_\-obj\-Vec)
\begin{CompactList}\small\item\em \begin{Desc}
\item[Warning:]NOT IMPLEMENTED, DO NOTHING ! Updates the fitness values of the whole population \_\-pop by taking the deletion of the objective vector \_\-obj\-Vec into account. \end{Desc}
\item\end{CompactList}\end{CompactItemize}
\subsection*{Private Member Functions}
\begin{CompactItemize}
\item 
void {\bf one\-Objective} ({\bf eo\-Pop}$<$ MOEOT $>$ \&\_\-pop)
\begin{CompactList}\small\item\em Sets the fitness values for mono-objective problems. \item\end{CompactList}\item 
void {\bf two\-Objectives} ({\bf eo\-Pop}$<$ MOEOT $>$ \&\_\-pop)
\begin{CompactList}\small\item\em Sets the fitness values for bi-objective problems with a complexity of O(n log n), where n stands for the population size. \item\end{CompactList}\item 
void {\bf m\-Objectives} ({\bf eo\-Pop}$<$ MOEOT $>$ \&\_\-pop)
\begin{CompactList}\small\item\em Sets the fitness values for problems with more than two objectives with a complexity of O(n\^{A}² log n), where n stands for the population size. \item\end{CompactList}\end{CompactItemize}
\subsection*{Private Attributes}
\begin{CompactItemize}
\item 
{\bf moeo\-Objective\-Vector\-Comparator}$<$ {\bf Objective\-Vector} $>$ \& {\bf comparator}\label{classmoeoFastNonDominatedSortingFitnessAssignment_cc2269f00944e308e53004cc3a68855b}

\begin{CompactList}\small\item\em Functor to compare two objective vectors. \item\end{CompactList}\item 
{\bf moeo\-Pareto\-Objective\-Vector\-Comparator}$<$ {\bf Objective\-Vector} $>$ {\bf pareto\-Comparator}\label{classmoeoFastNonDominatedSortingFitnessAssignment_c91bade0a1aa1200d0245f7c13fb74fc}

\begin{CompactList}\small\item\em Functor to compare two objective vectors according to Pareto dominance relation. \item\end{CompactList}\end{CompactItemize}


\subsection{Detailed Description}
\subsubsection*{template$<$class MOEOT$>$ class moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment$<$ MOEOT $>$}

Fitness assignment sheme based on Pareto-dominance count proposed in: N. 

Srinivas, K. Deb, \char`\"{}Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms\char`\"{}, Evolutionary Computation vol. 2, no. 3, pp. 221-248 (1994) and in: K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, \char`\"{}A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II\char`\"{}, IEEE Transactions on Evolutionary Computation, vol. 6, no. 2 (2002). This strategy is, for instance, used in NSGA and NSGA-II. 



Definition at line 29 of file moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment.h.

\subsection{Constructor \& Destructor Documentation}
\index{moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}!moeoFastNonDominatedSortingFitnessAssignment@{moeoFastNonDominatedSortingFitnessAssignment}}
\index{moeoFastNonDominatedSortingFitnessAssignment@{moeoFastNonDominatedSortingFitnessAssignment}!moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}}
\subsubsection{\setlength{\rightskip}{0pt plus 5cm}template$<$class MOEOT$>$ {\bf moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}$<$ MOEOT $>$::{\bf moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment} ({\bf moeo\-Objective\-Vector\-Comparator}$<$ {\bf Objective\-Vector} $>$ \& {\em \_\-comparator})\hspace{0.3cm}{\tt  [inline]}}\label{classmoeoFastNonDominatedSortingFitnessAssignment_6843abccb77386a06016063f42c63f75}


Ctor where you can choose your own way to compare objective vectors. 

\begin{Desc}
\item[Parameters:]
\begin{description}
\item[{\em \_\-comparator}]the functor used to compare objective vectors \end{description}
\end{Desc}


Definition at line 48 of file moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment.h.

\subsection{Member Function Documentation}
\index{moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}!operator()@{operator()}}
\index{operator()@{operator()}!moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}}
\subsubsection{\setlength{\rightskip}{0pt plus 5cm}template$<$class MOEOT$>$ void {\bf moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}$<$ MOEOT $>$::operator() ({\bf eo\-Pop}$<$ MOEOT $>$ \& {\em \_\-pop})\hspace{0.3cm}{\tt  [inline, virtual]}}\label{classmoeoFastNonDominatedSortingFitnessAssignment_4d75a10be83e50e4d3827c32b74f9d7d}


Sets the fitness values for every solution contained in the population \_\-pop. 

\begin{Desc}
\item[Parameters:]
\begin{description}
\item[{\em \_\-pop}]the population \end{description}
\end{Desc}


Implements {\bf eo\-UF$<$ eo\-Pop$<$ MOEOT $>$ \&, void $>$}.

Definition at line 56 of file moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment.h.

References moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment$<$ MOEOT $>$::m\-Objectives(), and moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment$<$ MOEOT $>$::one\-Objective().\index{moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}!updateByDeleting@{updateByDeleting}}
\index{updateByDeleting@{updateByDeleting}!moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}}
\subsubsection{\setlength{\rightskip}{0pt plus 5cm}template$<$class MOEOT$>$ void {\bf moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}$<$ MOEOT $>$::update\-By\-Deleting ({\bf eo\-Pop}$<$ MOEOT $>$ \& {\em \_\-pop}, {\bf Objective\-Vector} \& {\em \_\-obj\-Vec})\hspace{0.3cm}{\tt  [inline, virtual]}}\label{classmoeoFastNonDominatedSortingFitnessAssignment_8d16de444f6c7a73c28c9087b652656e}


\begin{Desc}
\item[Warning:]NOT IMPLEMENTED, DO NOTHING ! Updates the fitness values of the whole population \_\-pop by taking the deletion of the objective vector \_\-obj\-Vec into account. \end{Desc}


\begin{Desc}
\item[Parameters:]
\begin{description}
\item[{\em \_\-pop}]the population \item[{\em \_\-obj\-Vec}]the objective vector \end{description}
\end{Desc}
\begin{Desc}
\item[Warning:]NOT IMPLEMENTED, DO NOTHING ! \end{Desc}


Implements {\bf moeo\-Fitness\-Assignment$<$ MOEOT $>$} \doxyref{}{p.}{classmoeoFitnessAssignment_4922629569eddc9be049b3ead1ab0269}.

Definition at line 100 of file moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment.h.\index{moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}!oneObjective@{oneObjective}}
\index{oneObjective@{oneObjective}!moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}}
\subsubsection{\setlength{\rightskip}{0pt plus 5cm}template$<$class MOEOT$>$ void {\bf moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}$<$ MOEOT $>$::one\-Objective ({\bf eo\-Pop}$<$ MOEOT $>$ \& {\em \_\-pop})\hspace{0.3cm}{\tt  [inline, private]}}\label{classmoeoFastNonDominatedSortingFitnessAssignment_f69d3a918dbbe8d7e9ef5abc50fbf17b}


Sets the fitness values for mono-objective problems. 

\begin{Desc}
\item[Parameters:]
\begin{description}
\item[{\em \_\-pop}]the population \end{description}
\end{Desc}


Definition at line 120 of file moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment.h.

Referenced by moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment$<$ MOEOT $>$::operator()().\index{moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}!twoObjectives@{twoObjectives}}
\index{twoObjectives@{twoObjectives}!moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}}
\subsubsection{\setlength{\rightskip}{0pt plus 5cm}template$<$class MOEOT$>$ void {\bf moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}$<$ MOEOT $>$::two\-Objectives ({\bf eo\-Pop}$<$ MOEOT $>$ \& {\em \_\-pop})\hspace{0.3cm}{\tt  [inline, private]}}\label{classmoeoFastNonDominatedSortingFitnessAssignment_ac0337fe41c4d565c5a81de38398a9e9}


Sets the fitness values for bi-objective problems with a complexity of O(n log n), where n stands for the population size. 

\begin{Desc}
\item[Parameters:]
\begin{description}
\item[{\em \_\-pop}]the population \end{description}
\end{Desc}


Definition at line 136 of file moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment.h.\index{moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}!mObjectives@{mObjectives}}
\index{mObjectives@{mObjectives}!moeoFastNonDominatedSortingFitnessAssignment@{moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}}
\subsubsection{\setlength{\rightskip}{0pt plus 5cm}template$<$class MOEOT$>$ void {\bf moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment}$<$ MOEOT $>$::m\-Objectives ({\bf eo\-Pop}$<$ MOEOT $>$ \& {\em \_\-pop})\hspace{0.3cm}{\tt  [inline, private]}}\label{classmoeoFastNonDominatedSortingFitnessAssignment_f28ad92fe565e13b8d38a3beb30e1e29}


Sets the fitness values for problems with more than two objectives with a complexity of O(n\^{A}² log n), where n stands for the population size. 

\begin{Desc}
\item[Parameters:]
\begin{description}
\item[{\em \_\-pop}]the population \end{description}
\end{Desc}


Definition at line 146 of file moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment.h.

References moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment$<$ MOEOT $>$::comparator.

Referenced by moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment$<$ MOEOT $>$::operator()().

The documentation for this class was generated from the following file:\begin{CompactItemize}
\item 
moeo\-Fast\-Non\-Dominated\-Sorting\-Fitness\-Assignment.h\end{CompactItemize}
