Papers by Author: H. Hachimi

Abstract: In this paper, a new hybrid method of optimization by the heuristics algorithms to evaluate the reliability of the electronic card by simulating its thermo-mechanical behavior is presented. A model of simulation by finite element is developed to consider the maximal deformations due to temperature; a mechanico- computing coupling is used to find the optimal structure. Embedded electronic systems are playing a very important role in several areas, such as in automotive, aerospace, telecommunications and medical sectors. To properly perform their functions, electronic systems must be reliable [18].This powerful and robust algorithm which is based on hybridization of Differential Evolutionary algorithm with Particle Swarm Optimization (PSO) gives performance results [7].

Abstract: Embedded electronic systems are playing a very important role in several areas, such as in automotive, aerospace, telecommunications and medical sectors. To properly perform their functions, electronic systems must be reliable [2. So in this paper, we present a new hybrid method of optimization by the heuristics algorithms to evaluate the reliability of the electronic card by simulating its thermo-mechanical behavior. A model of simulation by finite element is developed to consider the maximal deformations due to the temperature; a mechanico-computing coupling is used to find the optimal structure. This powerful and robust algorithm which is based on hybridation of Genetic algorithm with Particle swarm optimization PSO gives performance results.

Abstract: In this paper, we present a new hybrid algorithm which is a combination of a hybrid genetic algorithm and particle swarm optimization. We focus in this research on a hybrid method combining two heuristic optimization techniques, genetic algorithms (GA) and particle swarm optimization (PSO) for the global optimization. Denoted as GA-PSO, this hybrid technique incorporates concepts from GA and PSO and creates individuals in a new generation not only by crossover and mutation operations as found in GA but also by mechanisms of PSO. The performance of the two algorithms has been evaluated using several experiments.