Bassem Jarboui

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The particle swarm optimization (PSO) has been widely used to solve continuous problems. The discrete problems have just begun to be also solved by the discrete PSO. However, the combinatorial problems remain a prohibitive area to the PSO mainly in case of integer values. In this paper, we propose a combinatorial PSO (CPSO) algorithm that we take up(More)
This paper presents a new clustering approach based on the combinatorial particle swarm optimization (CPSO) algorithm. Each particle is represented as a string of length n (where n is the number of data points) the ith element of the string denotes the group number assigned to object i. An integer vector corresponds to a candidate solution to the clustering(More)
The m-machine permutation flowshop problem PFSP with the objectives of minimizing the makespan and the total flowtime is a common scheduling problem, which is known to be NP-complete in the strong sense, when m P 3. This work proposes a new algorithm for solving the permutation FSP, namely combinatorial Particle Swarm Optimization. Furthermore, we(More)
In this paper, we consider the problem of scheduling n independent jobs on m uniform parallel machines such that total weighted completion time is minimized. We present two meta-heuristics and two hybrid meta-heuristics to solve this problem. Based on a set of instances, a comparative study has been realized in order to evaluate these approaches.
When handling combinatorial optimization problems, we try to get the optimal arrangement of discrete entities so that the requirements and the constraints are satisfied. These problems become more and more important in various industrial and academic fields. So, over the past years, several techniques have been proposed to solve them. In this paper, we are(More)
A hybrid genetic algorithm is proposed in this paper to minimize the makespan and the total flowtime in the no-wait flowshop scheduling problem, which is known to be NP-hard for more than two machines. The Variable Neighborhood Search is used as an improvement procedure in the last step of the genetic algorithm. First, comparisons are provided with respect(More)
The topic of modelling financial market price movements is in the heart of a wide ranging debate between fundamentalists and behaviourists. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the behaviour of two categories of traders. While the(More)