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Conception d'algorithmes hybrides pour l'optimisation de l'énergie mémoire dans les systèmes embarqués et de fonctions multimodales

Abstract : Résumé en anglais : Memory is considered to be greedy in energy consumption, a sensitive issue, especially in embedded systems. The global optimization of multimodal functions is also a difficult problem because of the large number of local optima of these functions. In this thesis report, I present various new hybrid and distributed algorithms to solve these two optimization problems. These algorithms are compared with conventional methods used in the literature and the results obtained are encouraging. Indeed, these results show a reduction in memory energy consumption by about 76% to more than 98% on our benchmarks on one hand. On the other hand, in the case of global optimization of multimodal functions, our hybrid algorithms converge more often to the global optimum solution. Distributed and cooperative versions of these new hybrid algorithms are also proposed. They are more faster than their respective sequential versions.
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Maha Idrissi Aouad. Conception d'algorithmes hybrides pour l'optimisation de l'énergie mémoire dans les systèmes embarqués et de fonctions multimodales. Autre [cs.OH]. Université Henri Poincaré - Nancy 1, 2011. Français. ⟨NNT : 2011NAN10029⟩. ⟨tel-01746175⟩

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