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@@ -45,8 +45,25 @@
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\section{Heuristics devlopped}
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\subsection{Fully random search (Test case)}
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- Blabla+pipeline
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- \subsection{The Knuth-Fisher-Yates shuffle}
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+ The first heuristic implemented is rge random search. We generates
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+ random sets of Halton points and select the best set with regard to its
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+ discrepancy iteratively. The process is wraped up in the following
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+ flowchart~\ref{rand_flow}. In order to generate at each step a random
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+ permutation, we transform it directly from the previous one.
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+ More precisely the permutation is a singleton object which have method
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+ random, built on the Knuth Fisher Yates shuffle. This algorithm allows
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+ us to generate an uniformly chosen permutation at each step. We recall
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+ this fact and detail the algorithm in the following section.
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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]{flow_rand.pdf}
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+\caption{Flowchart of the random search}
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+\end{mdframed}
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+\end{figure}
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+
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+
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+ \subsubsection{The Knuth-Fisher-Yates shuffle}
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The Fisher–Yates shuffle is an algorithm for generating a random permutation
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of a finite sets. The Fisher–Yates shuffle is unbiased, so that every
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@@ -86,6 +103,9 @@ the naive implementation.
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algorithm is thus unbiaised.
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\end{proof}
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+
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+
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+\subsubsection{Results and stability}
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\subsection{Local Search}
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Blabla+Pipeline
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\subsection{Evolutionary heuristics}
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espitau