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[book_gpu.git] / BookGPU / Chapters / chapter8 / ch8.tex

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 \chapterauthor{Nouredine Melab}{Universit\'e Lille 1 CNRS/LIFL, INRIA Lille Nord Europe, Cit\'e scientifique - 59655, Villeneuve d'Ascq cedex, France\\}
 
 \chapter{GPU-accelerated Tree-based Exact Optimization Methods}
 \chapterauthor{Nouredine Melab}{Universit\'e Lille 1 CNRS/LIFL, INRIA Lille Nord Europe, Cit\'e scientifique - 59655, Villeneuve d'Ascq cedex, France\\}
 
 \chapter{GPU-accelerated Tree-based Exact Optimization Methods}

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+\label{ch8:GPU-accelerated-tree-based-exact-optimization-methods}

 \section{Introduction}
 \label{ch8:introduction}
 
 \section{Introduction}
 \label{ch8:introduction}
 


@@ -858,4 +858,4 @@ Experiments show also that the proposed refactoring approach improves the parall
 
 In the near future, we plan to extend this work to a cluster of GPU-accelerated multi-core processors. From the application point of view, the objective is to optimally solve challenging and unsolved Flow-Shop instances as we did it for one 50$\times$20 problem instance with grid computing \cite{ch8:Mezmaz_2007}. Finally, we plan to investigate other lower bound functions to deal with other combinatorial optimization problems. 
 
 
 In the near future, we plan to extend this work to a cluster of GPU-accelerated multi-core processors. From the application point of view, the objective is to optimally solve challenging and unsolved Flow-Shop instances as we did it for one 50$\times$20 problem instance with grid computing \cite{ch8:Mezmaz_2007}. Finally, we plan to investigate other lower bound functions to deal with other combinatorial optimization problems. 
 

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