-\chapterauthor{Malika Mehdi and Ahc\`{e}ne Bendjoudi}{CERIST Research Center, DTISI, 3 rue des frères Aissou, 16030 Ben-Aknoun, Algiers, Algeria}
+\chapterauthor{Malika Mehdi and Ahc\`{e}ne Bendjoudi}{CERIST Research Center, Algiers, Algeria}
\chapterauthor{Lakhdar Loukil}{University of Oran, Algeria}
%\chapterauthor{Ahc\`{e}ne Bendjoudi}{CERIST Research Center, DTISI, 3 rue des frères Aissou, 16030 Ben-Aknoun, Algiers, Algeria}
-\chapterauthor{Nouredine Melab}{Université Lille 1, LIFL/UMR CNRS 8022, 59655-Villeneuve d'Ascq cedex, France}
+\chapterauthor{Nouredine Melab}{University of Lille 1, CNRS/LIFL/INRIA, France}
\chapter{Parallel GPU-accelerated metaheuristics}
\label{chapter9}
satisfied. \emph{Evolutionary algorithms}, \emph{swarm
optimization}, and \emph{ant colonies} fall into this class.
-
+\clearpage
\section{Parallel models for metaheuristics}\label{ch8:sec:paraMeta}
Optimization problems, whether real-life or academic, are more
often NP-hard and CPU time and/or memory consuming. Metaheuristics
parallel model is problem-dependent.}
\end{itemize}
\clearpage
-\section{Challenges for the design of GPU-based metaheuristics}
+\section[Challenges for the design of GPU-based metaheuristics]{Challenges for the design of GPU-based\hfill\break metaheuristics}
\label{ch8:sec:challenges}
Developing GPU-based parallel
achieved by the GPU implementation compared
to the same sequential implementation on CPU using SA-matrix.
-\subsection[Implementing population-based metaheuristics\hfill\break on GPUs]{Implementing population-based metaheuristics on GPUs}
+\subsection[Implementing population-based metaheuristics on GPUs]{Implementing population-based metaheuristics on GPUs}
State-of-the-art works dealing with the implementation of
p-metaheuristics on GPUs generally rely on parallel models and
