\hypertarget{classmoeo_hypervolume_binary_metric}{}\doxysection{moeo\+Hypervolume\+Binary\+Metric$<$ Objective\+Vector $>$ Class Template Reference} \label{classmoeo_hypervolume_binary_metric}\index{moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$@{moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$}} {\ttfamily \#include $<$moeo\+Hypervolume\+Binary\+Metric.\+h$>$} Inheritance diagram for moeo\+Hypervolume\+Binary\+Metric$<$ Objective\+Vector $>$\+: \nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=350pt]{classmoeo_hypervolume_binary_metric__inherit__graph} \end{center} \end{figure} Collaboration diagram for moeo\+Hypervolume\+Binary\+Metric$<$ Objective\+Vector $>$\+: \nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=350pt]{classmoeo_hypervolume_binary_metric__coll__graph} \end{center} \end{figure} \doxysubsection*{Public Member Functions} \begin{DoxyCompactItemize} \item \mbox{\hyperlink{classmoeo_hypervolume_binary_metric_a01a07711a7c9f38cdc2c76e40a3c5958}{moeo\+Hypervolume\+Binary\+Metric}} (double \+\_\+rho=1.\+1) \item double \mbox{\hyperlink{classmoeo_hypervolume_binary_metric_ac147309a5ba6b365be926e6083c5b9f2}{operator()}} (const \mbox{\hyperlink{classmoeo_real_objective_vector}{Objective\+Vector}} \&\+\_\+o1, const \mbox{\hyperlink{classmoeo_real_objective_vector}{Objective\+Vector}} \&\+\_\+o2) \end{DoxyCompactItemize} \doxysubsection*{Additional Inherited Members} \doxysubsection{Detailed Description} \subsubsection*{template$<$class Objective\+Vector$>$\newline class moeo\+Hypervolume\+Binary\+Metric$<$ Objective\+Vector $>$} Hypervolume binary metric allowing to compare two objective vectors as proposed in Zitzler E., Künzli S.\+: Indicator-\/\+Based Selection in Multiobjective Search. In Parallel \mbox{\hyperlink{class_problem}{Problem}} Solving from Nature (P\+P\+SN V\+I\+II). Lecture Notes in Computer Science 3242, Springer, Birmingham, UK pp.\+832–842 (2004). This indicator is based on the hypervolume concept introduced in Zitzler, E., Thiele, L.\+: Multiobjective Optimization Using Evolutionary Algorithms -\/ A Comparative Case Study. Parallel \mbox{\hyperlink{class_problem}{Problem}} Solving from Nature (P\+P\+S\+N-\/V), pp.\+292-\/301 (1998). This code is adapted from the P\+I\+SA implementation of I\+B\+EA (\href{http://www.tik.ee.ethz.ch/sop/pisa/}{\texttt{ http\+://www.\+tik.\+ee.\+ethz.\+ch/sop/pisa/}}) \doxysubsection{Constructor \& Destructor Documentation} \mbox{\Hypertarget{classmoeo_hypervolume_binary_metric_a01a07711a7c9f38cdc2c76e40a3c5958}\label{classmoeo_hypervolume_binary_metric_a01a07711a7c9f38cdc2c76e40a3c5958}} \index{moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$@{moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$}!moeoHypervolumeBinaryMetric@{moeoHypervolumeBinaryMetric}} \index{moeoHypervolumeBinaryMetric@{moeoHypervolumeBinaryMetric}!moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$@{moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$}} \doxysubsubsection{\texorpdfstring{moeoHypervolumeBinaryMetric()}{moeoHypervolumeBinaryMetric()}} {\footnotesize\ttfamily template$<$class Objective\+Vector $>$ \\ \mbox{\hyperlink{classmoeo_hypervolume_binary_metric}{moeo\+Hypervolume\+Binary\+Metric}}$<$ \mbox{\hyperlink{classmoeo_real_objective_vector}{Objective\+Vector}} $>$\+::\mbox{\hyperlink{classmoeo_hypervolume_binary_metric}{moeo\+Hypervolume\+Binary\+Metric}} (\begin{DoxyParamCaption}\item[{double}]{\+\_\+rho = {\ttfamily 1.1} }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Ctor \begin{DoxyParams}{Parameters} {\em \+\_\+rho} & value used to compute the reference point from the worst values for each objective (default \+: 1.\+1) \\ \hline \end{DoxyParams} \doxysubsection{Member Function Documentation} \mbox{\Hypertarget{classmoeo_hypervolume_binary_metric_ac147309a5ba6b365be926e6083c5b9f2}\label{classmoeo_hypervolume_binary_metric_ac147309a5ba6b365be926e6083c5b9f2}} \index{moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$@{moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$}!operator()@{operator()}} \index{operator()@{operator()}!moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$@{moeoHypervolumeBinaryMetric$<$ ObjectiveVector $>$}} \doxysubsubsection{\texorpdfstring{operator()()}{operator()()}} {\footnotesize\ttfamily template$<$class Objective\+Vector $>$ \\ double \mbox{\hyperlink{classmoeo_hypervolume_binary_metric}{moeo\+Hypervolume\+Binary\+Metric}}$<$ \mbox{\hyperlink{classmoeo_real_objective_vector}{Objective\+Vector}} $>$\+::operator() (\begin{DoxyParamCaption}\item[{const \mbox{\hyperlink{classmoeo_real_objective_vector}{Objective\+Vector}} \&}]{\+\_\+o1, }\item[{const \mbox{\hyperlink{classmoeo_real_objective_vector}{Objective\+Vector}} \&}]{\+\_\+o2 }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}, {\ttfamily [virtual]}} Returns the volume of the space that is dominated by \+\_\+o2 but not by \+\_\+o1 with respect to a reference point computed using rho. \begin{DoxyWarning}{Warning} don\textquotesingle{}t forget to set the bounds for every objective before the call of this function \end{DoxyWarning} \begin{DoxyParams}{Parameters} {\em \+\_\+o1} & the first objective vector \\ \hline {\em \+\_\+o2} & the second objective vector \\ \hline \end{DoxyParams} Implements \mbox{\hyperlink{classeo_b_f_aa03c40b95210569b826df79a2237a0d0}{eo\+B\+F$<$ const Objective\+Vector \&, const Objective\+Vector \&, double $>$}}. The documentation for this class was generated from the following file\+:\begin{DoxyCompactItemize} \item moeo/src/metric/moeo\+Hypervolume\+Binary\+Metric.\+h\end{DoxyCompactItemize}