Facteurs Predictifs De Malignite D\'un Nodule Thyroidien

Buts : étudier les facteurs prédictifs de malignité des nodules thyroïdiens et comparer nos résultats à ceux de la littérature. Patients et méthodes : Il s\'agit d\'une étude rétrospective a propos de 282 cas de nodules thyroïdiens opérés à l\' hôpital de Mahdia entre 1988 et 2003. Résultats : L\'âge moyen était de 44 ans. Le risque de malignité des nodules thyroïdiens était de 15,6% . Ce risque était plus important chez les hommes (50%) que chez les femmes (13,3%). Certains facteurs étaient hautement prédictifs de malignité comme l\'âge supérieur à 60 ans, les signes de compression, les adénopathies cervicales et le caractère fixe et dure du nodule thyroidien Conclusion : Certains signes cliniques et para cliniques ont une grande valeur en matière de bénignité ou de malignité des nodules thyroïdiens.Aim : Study the predictive factors of malignancy of thyroid gland nodules and compare our results to those of the literature. Patients and methods : A retrospective study about 282 cases of thyroid gland nodules treated in Madhya hospital between 1988 and 2003. Results : The middle age was 44 years. The risk of malignancy was 15,6 %. This risk was higher in men (50 %) then in women (13,3 %). Some factors were highly predictive of malignancy like age superior then 60 years, neck lymph nodes … Conclusion: Some clinic and para clinic signs have an important value in benignancy or malignancy of thyroid gland nodules. Journal Tunisien d\'ORL et de chirurgie cervico-faciale Vol. 18 2007: pp. 20-2

An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem

The flexible job shop scheduling problem (FJSP) is vital to manufacturers especially in today’s constantly changing environment. It is a strongly NP-hard problem and therefore metaheuristics or heuristics are usually pursued to solve it. Most of the existing metaheuristics and heuristics, however, have low efficiency in convergence speed. To overcome this drawback, this paper develops an elitist quantum-inspired evolutionary algorithm. The algorithm aims to minimise the maximum completion time (makespan). It performs a global search with the quantum-inspired evolutionary algorithm and a local search with a method that is inspired by the motion mechanism of the electrons around an atomic nucleus. Three novel algorithms are proposed and their effect on the whole search is discussed. The elitist strategy is adopted to prevent the optimal solution from being destroyed during the evolutionary process. The results show that the proposed algorithm outperforms the best-known algorithms for FJSPs on most of the FJSP benchmarks

Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

Abstract The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based clustered holonic multiagent model. First, a neighborhood-based genetic algorithm (NGA) is applied by a scheduler agent for a global exploration of the search space. Second, a local search technique is used by a set of cluster agents to guide the research in promising regions of the search space and to improve the quality of the NGA final population. The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions. Computational results are presented using four sets of well-known benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach