Literatura científica selecionada sobre o tema "Problème d'optimisation non linéaire"
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Artigos de revistas sobre o assunto "Problème d'optimisation non linéaire"
Blanpain, O., L. Petit, J. Le Gouevec e S. Merchez. "Une approche pour l'approximation du profil en long des réseaux d'assainissement à partir de données incomplètes". Revue des sciences de l'eau 12, n.º 4 (12 de abril de 2005): 661–69. http://dx.doi.org/10.7202/705371ar.
Texto completo da fonteRaïssi, Nadia, e Mustapha Serhani. "Algorithme de dualité pour un problème d'optimisation non convexe : application à un problème de Stokes non linéaire". Comptes Rendus de l'Académie des Sciences - Series I - Mathematics 333, n.º 8 (outubro de 2001): 801–6. http://dx.doi.org/10.1016/s0764-4442(01)02130-9.
Texto completo da fonteAit-Ouyahia, Hamid. "Allocation de l'effort de visite: une approche à base de connaissance issue des méthodes de portefeuille et d'optimisation". Recherche et Applications en Marketing (French Edition) 12, n.º 3 (setembro de 1997): 39–46. http://dx.doi.org/10.1177/076737019701200303.
Texto completo da fonteLe Brizaut, Jean-Sébastien. "Méthodes d'optimisation pour l'approche de problèmes aux limites non linéaires mixtes elliptiques hyperboliques". Bulletin des Sciences Mathématiques 127, n.º 3 (maio de 2003): 231–50. http://dx.doi.org/10.1016/s0007-4497(03)00018-6.
Texto completo da fonteKerdid, Nabil, Hervé Le Dret e Abdelkader Saïdi. "Approximation numérique d'un problème de membrane non linéaire". Comptes Rendus Mathematique 340, n.º 1 (janeiro de 2005): 69–74. http://dx.doi.org/10.1016/j.crma.2004.11.016.
Texto completo da fonteYuan, X., S. Zhang, L. Pibouleau e S. Domenech. "Une méthode d'optimisation non linéaire en variables mixtes pour la conception de procédés". RAIRO - Operations Research 22, n.º 4 (1988): 331–46. http://dx.doi.org/10.1051/ro/1988220403311.
Texto completo da fonteOuaro, Stanislas, e Hamidou Touré. "Sur un problème de type elliptique parabolique non linéaire". Comptes Rendus Mathematique 334, n.º 1 (janeiro de 2002): 27–30. http://dx.doi.org/10.1016/s1631-073x(02)02198-2.
Texto completo da fonteJeribi, Aref. "Un problème non linéaire intervenant en dynamique des populations". Comptes Rendus de l'Académie des Sciences - Series I - Mathematics 330, n.º 9 (maio de 2000): 795–800. http://dx.doi.org/10.1016/s0764-4442(00)00269-x.
Texto completo da fonteBenaouda, A., A. Gmira e B. Hamri. "Classification des solutions d’un problème elliptique fortement non linéaire". Annales mathématiques Blaise Pascal 12, n.º 1 (2005): 161–80. http://dx.doi.org/10.5802/ambp.200.
Texto completo da fonteKoko, Jonas. "Décomposition par dualisation d'un problème non linéaire de bassin sédimentaire". ESAIM: Proceedings 20 (2007): 149–56. http://dx.doi.org/10.1051/proc:072014.
Texto completo da fonteTeses / dissertações sobre o assunto "Problème d'optimisation non linéaire"
Krzesaj, Michel. "Modélisation et résolution de problèmes d'optimisation non linéaire de grande taille". Lille 1, 1985. http://www.theses.fr/1985LIL10070.
Texto completo da fonteDelbos, Frédéric. "Problèmes d'Optimisation Non Linéaire avec Contraintes en Tomographie de Réflexion 3D". Paris 6, 2004. http://www.theses.fr/2004PA066082.
Texto completo da fonteDayde, Michel. "Parallélisation d'algorithmes d'optimisation pour des problèmes de conception optimale". Toulouse, INPT, 1986. http://www.theses.fr/1986INPT030H.
Texto completo da fonteReneaume, Jean-Michel. "Formulation et résolution du problème d'optimisation non linéaire en variables mixtes dans un environnement modulaire. Application à la synthèse optimale des procédés". Toulouse, INPT, 1995. http://www.theses.fr/1995INPT042G.
Texto completo da fonteKiwan, Rola. "Problèmes d'optimisation liés aux valeurs propres du Laplacien et aux pavages du plan [et] problèmes d'évolutions semi-linéaires". Tours, 2007. http://www.theses.fr/2007TOUR4001.
Texto completo da fonteIn this thesis, we consider first the optimal placement problem for the first Dirichlet Laplacian eingenvalue for plane domains with dihidral symetry, we then consider the same problem for the second eigenvalue of spherical shells. We solve the isoperimetric problem for plane domains who tile the plane by the action of a given lattice. Finally we study sufficient conditions for explosion in finite time for the solution of a non local parabolic problem as well as hyperbolic inequality
Tamby, Satya. "Approches génériques pour la résolution de problèmes d'optimisation discrète multiobjectif". Electronic Thesis or Diss., Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLED048.
Texto completo da fonteReal world problems often involve several conflicting objectives. Thus, solution of interests are efficient solutions which have the property that an improvement on one objective leads to a decay on another one. The image of such solutions are referred to as nondominated points. We consider here the standard problem of computing the set of nondominated points, and providing a corresponding efficient solution for each point
Migot, Tangi. "Contributions aux méthodes numériques pour les problèmes de complémentarité et problèmes d'optimisation sous contraintes de complémentarité". Thesis, Rennes, INSA, 2017. http://www.theses.fr/2017ISAR0026/document.
Texto completo da fonteIn this thesis, we studied the regularization methods for the numerical resolution of problems with equilibria. In the first part, we focused on the complementarity problems through two applications that are the absolute value equation and the sparse optimization problem. In the second part, we concentrated on optimization problems with complementarity constraints. After studying the optimality conditions of this problem, we proposed a new regularization method, so-called butterfly relaxation. Then, based on an analysis of the regularized sub-problems we defined an algorithm with strong convergence property. Throughout the manuscript, we concentrated on the theoretical properties of the algorithms as well as their numerical applications. In the last part of this document, we presented numerical results using the regularization methods for the mathematical programs with complementarity constraints
Anani, Kwami Dodzivi. "Diagnostic de systèmes non linéaires par analyse en composantes principales à noyau". Thesis, Université de Lorraine, 2019. http://www.theses.fr/2019LORR0026/document.
Texto completo da fonteIn this thesis, the diagnosis of a nonlinear system was performed using data analysis. Initially developed to analyze linear system, Principal Component Analysis (PCA) is coupled with kernel methods for detection, isolation and estimation of faults' magnitude for nonlinear systems. Kernel PCA consists in projecting data using a nonlinear mapping function into a higher dimensional space called feature space where the linear PCA is applied. Due to the fact that the projections are done using kernels, the detection can be performed in the feature space. However, estimating the magnitude of the fault requires the resolution of a nonlinear optimization problem. The variables' contributions make it possible to isolate and estimate these magnitudes. The variable with the largest contribution may be considered as faulty. In our work, we proposed new methods for the isolation and estimation phases for which previous work has some limitations. The new proposed method in this thesis is based on contributions under constraints. The effectiveness of the developed methods is illustrated on the simulated continuous stirred tank reactor (CSTR)
Del, Moral Pierre. "Résolution particulaire des problèmes d'estimation et d'optimisation non-linéaires". Toulouse 3, 1994. http://www.theses.fr/1994TOU30075.
Texto completo da fonteWu, Dawen. "Solving Some Nonlinear Optimization Problems with Deep Learning". Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG083.
Texto completo da fonteThis thesis considers four types of nonlinear optimization problems, namely bimatrix games, nonlinear projection equations (NPEs), nonsmooth convex optimization problems (NCOPs), and chance-constrained games (CCGs).These four classes of nonlinear optimization problems find extensive applications in various domains such as engineering, computer science, economics, and finance.We aim to introduce deep learning-based algorithms to efficiently compute the optimal solutions for these nonlinear optimization problems.For bimatrix games, we use Convolutional Neural Networks (CNNs) to compute Nash equilibria.Specifically, we design a CNN architecture where the input is a bimatrix game and the output is the predicted Nash equilibrium for the game.We generate a set of bimatrix games by a given probability distribution and use the Lemke-Howson algorithm to find their true Nash equilibria, thereby constructing a training dataset.The proposed CNN is trained on this dataset to improve its accuracy. Upon completion of training, the CNN is capable of predicting Nash equilibria for unseen bimatrix games.Experimental results demonstrate the exceptional computational efficiency of our CNN-based approach, at the cost of sacrificing some accuracy.For NPEs, NCOPs, and CCGs, which are more complex optimization problems, they cannot be directly fed into neural networks.Therefore, we resort to advanced tools, namely neurodynamic optimization and Physics-Informed Neural Networks (PINNs), for solving these problems.Specifically, we first use a neurodynamic approach to model a nonlinear optimization problem as a system of Ordinary Differential Equations (ODEs).Then, we utilize a PINN-based model to solve the resulting ODE system, where the end state of the model represents the predicted solution to the original optimization problem.The neural network is trained toward solving the ODE system, thereby solving the original optimization problem.A key contribution of our proposed method lies in transforming a nonlinear optimization problem into a neural network training problem.As a result, we can now solve nonlinear optimization problems using only PyTorch, without relying on classical convex optimization solvers such as CVXPY, CPLEX, or Gurobi
Livros sobre o assunto "Problème d'optimisation non linéaire"
Bifurcation of extremals in optimal control. Berlin: Springer-Verlag, 1986.
Encontre o texto completo da fonteV, Zhitarashu N., ed. Parabolic boundary value problems. Basel: Birkhäuser Verlag, 1998.
Encontre o texto completo da fonteEidelman, Samuil D., e Nicolae V. Zhitarashu. Parabolic Boundary Value Problems (Operator Theory: Advances and Applications). Birkhauser, 1999.
Encontre o texto completo da fonteEidelman, Samuil D. Parabolic Boundary Value Problems. Birkhäuser, 2012.
Encontre o texto completo da fonteEidelman, Samuil D., e Nicolae V. Zhitarashu. Parabolic Boundary Value Problems. Birkhauser Verlag, 2012.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Problème d'optimisation non linéaire"
Gourdin, Daniel, e Mustapha Mechab. "Large Temps de vie des Solutions D’un Problème de Cauchy Non Linéaire". In Jean Leray ’99 Conference Proceedings, 65–74. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-2008-3_5.
Texto completo da fontede Oliveira, Paula Milheiro. "Filtres approchés pour un problème de filtrage non linéaire discret avec petit bruit d’observation". In Analysis and Optimization of Systes, 198–207. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/bfb0120042.
Texto completo da fonte