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\label{s.ffa}  The Firefly Algorithm (FFA)~\cite{Yang_2010} is a meta-heuristic optimization technique inspired by the flashing behavior of fireflies, which attempt at flashing in order to attract possible mates. Let $\textbf{x}_i^t$ be the position of firefly (agent) $i$ at iteration $t$. Roughly speaking, the idea of FFA is to move agents towards brighter ones, i.e., agents with lower fitness functions, as follows:  %\textbf{x}^t_i+\psi %  e^{-\tau d_{i,j}^2}(\textbf{x}^t_j-\textbf{x}^t_i)+\eta^t\bm{\lambda}^t_i %  \begin{eqnarray}  \label{e.position_ffa}  \textbf{x}^{t+1}_i & = & \left\{ \begin{array}{ll} \textbf{x}^t_i +\psi  & \mbox{{ if $f(\textbf{x}_i^t)  \end{array}\right.  \end{eqnarray}