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\end{eqnarray}  The pitch adjustment is often used to improve solutions and to escape from local optima. This mechanism concerns shifting the neighboring values of some decision variable in the harmony, where $\varrho$ is an arbitrary distance bandwidth, and $\varphi_j\sim {\cal U}(0,1)$.  \begin{eqnarray}  \label{eq:par}  \hat{\phi}^j & = & \left\{ \begin{array}{ll} \hat{\phi}^j\pm \varphi_j \varrho & \mbox{{ with probability PAR}} \\  \hat{\phi}^j & \mbox{{ with probability (1-PAR).}}  \end{array}\right.  \end{eqnarray}  The pitch adjustment is often used to improve solutions and to escape from local optima. This mechanism concerns shifting the neighbouring values of some decision variable in the harmony, where $\varrho$ is an arbitrary distance bandwidth, and $\varphi_j\sim {\cal U}(0,1)$. Below, we briefly present some variants of the vanilla Harmony Search employed in this work.  \paragraph{Improved Harmony Search}  \label{ss.ihs}  The Improved Harmony Search (IHS)~ differs from traditional HS by updating the PAR and $\varrho$ values dynamically. The PAR updating formulation at time step $t$ is given by:  \begin{equation}  \label{e.par_updating}  PAR^t = PAR_{min}+\frac{PAR_{max}-PAR_{min}}{T}t,  \end{equation}  where $T$ stands for the number of iterations, and $PAR_{min}$ and $PAR_{max}$ denote the minimum and maximum PAR values, respectively. In regard to the bandwidth value at time step $t$, it is computed as follows:  \begin{equation}  \label{e.bandwidth_updating}  \varrho^t=\varrho_{max}\exp{\frac{\ln(\varrho_{min}/\varrho_{max})}{T}t},  \end{equation}  where $\varrho_{min}$ and $\varrho_{max}$ stand for the minimum and maximum values of $\varrho$, respectively.  \section*{Acknowledgments}  The authors are grateful to FAPESP grants \#2013/20387-7 and \#2014/16250-9, as well as CNPq grants \#470571/2013-6 and \#306166/2014-3.