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Contribution aux méthodes hybrides d'optimisation heuristique : Distribution et application à l'interopérabilité des systèmes d'information

Abstract : The work presented in this PhD thesis contibutes to a new method for a modified particle swarm optimization algorith (MPSO) combined with a simulating annealing algorithm (SA). MPSO is known as an efficient approach with a high performance of solving optimization problems in many research fields. It is a population intelligence algorithm [Eberhart et Kennedy (1995)] inspired by social behavior simulations of bird flocking. Considerable research work on classical method PSO (Particle Swarm Optimization) has been done to improve the performance of this method. Therefore, the propose hybrid optimization algorithms MPSOSA use the combination of MPSO and simulating annealing SA. This method has the avantage to provide best results comparing with all heuristics methods PSO and SA. In this matter, a benchmark of eighteen well-known functions is given. These functions present different situations of finding the global minimum with gradual difficulties. Numerical results presented, in this paper, show the robustness of the MPSOSA algorithm. Numerical comparisons with three algorithms namely, Simulating Annealing, Modified Particle swarm optimization and MPSO-SA show that hybrid algorithm offers better results. This method (MPSO-SA) treats a wide range of optimization problems, in information systems interoperability and in structural optimization field.
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https://tel.archives-ouvertes.fr/tel-00771360
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  • HAL Id : tel-00771360, version 1

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Norelislam El Hami. Contribution aux méthodes hybrides d'optimisation heuristique : Distribution et application à l'interopérabilité des systèmes d'information. Autre [cs.OH]. INSA de Rouen; École Mohammadia d'ingénieurs (Rabat, Maroc), 2012. Français. ⟨NNT : 2012ISAM0009⟩. ⟨tel-00771360⟩

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