Jaafar Abouchabaka

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The genetic algorithm includes some parameters that should be adjusted, so as to get reliable results. Choosing a representation of the problem addressed, an initial population, a method of selection, a crossover operator, mutation operator, the probabilities of crossover and mutation, and the insertion method creates a variant of genetic algorithms. Our(More)
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure. As the real-time applications used in today's wireless network grow, we need some schemes to provide more suitable service for them. We know that most of actual schemes do not perform well on traffic which is not strictly CBR. Therefore, in this paper we(More)
Genetic algorithm includes some parameters that should be adjusting so that the algorithm can provide positive results. Crossover operators play very important role by constructing competitive Genetic Algorithms (GAs). In this paper, the basic conceptual features and specific characteristics of various crossover operators in the context of the Traveling(More)
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure. Despite the importance of type of the exchanged data between the knots on the QoS of the MANETs, the mul-tiservice data were not treated by the larger number of previous researches. In this paper we propose an adaptive method which gives the best(More)
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure. As the real-time applications used in today's wireless network grow, we need some schemes to provide more suitable service for them. We know that most of actual schemes do not perform well on traffic which is not strictly CBR. Therefore, in this paper we(More)
The genetic algorithm includes some parameters that should be adjusted, so as to get reliable results. Choosing a representation of the problem addressed, an initial population, a method of selection, a crossover operator, mutation operator, the probabilities of crossover and mutation, and the insertion method creates a variant of genetic algorithms. Our(More)
The Multi Agent Systems are a paradigm of the most promising technology in the development of distributed software systems. They include the mechanisms and functions required to support interaction, communication and coordination between the various components of such a system. In the context of distributed test the activity of the test is performed by a(More)
The aim of this work is to present a meta-heuristically approach of the spatial assignment problem of human resources in multi-sites enterprise. Usually, this problem consists to move employees from one site to another based on one or more criteria. Our goal in this new approach is to improve the quality of service and performance of all sites with(More)
In this paper, we present the  GD-calculus witch is an elementary functional distributed agent language with a new approach of messages communication between agents in a distributed environment. This strategy is based on a static analysis which allows determining the parts of a message that must be transmitted. The agents we consider have a functional(More)
In this paper, we present a new mutation operator, Hybrid Mutation (HPRM), for a genetic algorithm that generates high quality solutions to the Traveling Salesman Problem (TSP). The Hybrid Mutation operator constructs an offspring from a pair of parents by hybridizing two mutation operators, PSM and RSM. The efficiency of the HPRM is compared as against(More)