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Дисертації з теми "Contraintes de cardinalité":
Barcenas, Patino Ismael. "Raisonnement automatisé sur les arbres avec des contraintes de cardinalité." Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00569058.
Barcenas, Everardo. "Raisonnement automatisé sur les arbres avec des contraintes de cardinalité." Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00578972.
Lo, Bianco Accou Giovanni Christian. "Estimating the number of solutions on cardinality constraints." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2019. http://www.theses.fr/2019IMTA0155/document.
The main asset of constraint programming is its wide variety of algorithms that comes from the major areas of artificial intelligence, logic programming and operational research. It offers specialists a limitless range of possible configurations to tackle combinatorial problems, but it becomes an obstacle to the wider diffusion of the paradigm. The current tools are very far from being used as a black-box tool, and it assumes a good knowledge of the field, in particular regarding the parametrization of solvers.In this thesis, we propose to analyze the behavior of cardinality constraints with probabilistic models and counting tools, to automatically parameterize constraint solvers: heuristics of choice of variables and choice of values and search strategies
Moeini, Mahdi. "La programmation DC et DCA pour l'optimisation de portefeuille." Thesis, Metz, 2008. http://www.theses.fr/2008METZ008S/document.
The topics presented in this thesis are related to new optimization techniques for solving some challenging problems resulting from finance. They are large-scale non convex optimization problems for which finding efficient solving methods is currently the topic of numerous researches. Our work is based mainly on DC (Difference of Convex functions) programming and DCA (DC Algorithm). This approach is motivated by the robustness and efficiency of DC programming and DCA approaches in comparison to the other methods. The thesis is divided into two parts and consists of seven chapters. In the first part entitled Methodology ; we present theoretical tools and algorithms that we are going to use in the thesis. The first chapter is about DC programming and DCA and the second focuses on branch and bound algorithms. In the second part we develop DC programming and DCA for solving some problems in finance. We begin with an introduction to the modern portfolio theory (The Chapter 3). The Chapter 4 is dedicated to the generalizations of the mean variance (MV) model of Markowitz, where we study the MV model under the buy-in threshold constraints, threshold constraints, and cardinality constraints. The Chapter 5 is devoted to the portfolio selection problem under downside risk measure and cardinality constraints. The Chapter 6 deals with the portfolio optimization under step increasing transaction costs functions. Finally, the robust investment strategies with discrete asset choice constraints are developed in the last chapter
Lasluisa, Daniel. "Contributions to optimization in energy : from bilevel optimization to optimal design of renewable energy plant." Electronic Thesis or Diss., Perpignan, 2024. http://www.theses.fr/2024PERP0009.
In this thesis work, we develop and apply optimization techniques in energy design and management. First we focus on bilevel optimization and developed new theoretical analysis for single-leader-multi-follower games with cardinality constraints. It is then applied to optimal location of charging stations for electric vehicles. The second part is dedicated to economic optimization of solar power plants from a long term as well as from a short term perspective. Innovating global optimization approach mixing optimal design of storage and optimal operation in a market context is developed. Then at a short term scale, the optimal control of energy production of a solar power plant is analysed
En este trabajo de tesis, desarrollamos y aplicamos técnicas de optimización en el dise˜no y gestión de energía. En primer lugar, nos enfocamos en la optimización binivel y desarrollamos nuevo análisis teórico para single-leader-multi-follower games con restricciones de cardinalidad. Luego, se aplica a la localización óptima de estaciones de carga por vehículos eléctricos. La segunda parte está dedicada a la optimización económica de plantas solares desde una perspectiva a largo plazo, así como desde una perspectiva a corto plazo. Se desarrolla un enfoque innovador de optimización global que combina el dise˜no óptimo de almacenamiento y la operación óptima en un contexto de mercado. Luego, a escala a corto plazo, se analiza el control óptimo de la producción de energía de una planta solar
Moeini, Mahdi. "La programmation DC et DCA pour l'optimisation de portefeuille." Electronic Thesis or Diss., Metz, 2008. http://www.theses.fr/2008METZ008S.
The topics presented in this thesis are related to new optimization techniques for solving some challenging problems resulting from finance. They are large-scale non convex optimization problems for which finding efficient solving methods is currently the topic of numerous researches. Our work is based mainly on DC (Difference of Convex functions) programming and DCA (DC Algorithm). This approach is motivated by the robustness and efficiency of DC programming and DCA approaches in comparison to the other methods. The thesis is divided into two parts and consists of seven chapters. In the first part entitled Methodology ; we present theoretical tools and algorithms that we are going to use in the thesis. The first chapter is about DC programming and DCA and the second focuses on branch and bound algorithms. In the second part we develop DC programming and DCA for solving some problems in finance. We begin with an introduction to the modern portfolio theory (The Chapter 3). The Chapter 4 is dedicated to the generalizations of the mean variance (MV) model of Markowitz, where we study the MV model under the buy-in threshold constraints, threshold constraints, and cardinality constraints. The Chapter 5 is devoted to the portfolio selection problem under downside risk measure and cardinality constraints. The Chapter 6 deals with the portfolio optimization under step increasing transaction costs functions. Finally, the robust investment strategies with discrete asset choice constraints are developed in the last chapter
Derhy, Nicolas. "Multicoupes et sous-graphes induits : complexité et algorithmes." Phd thesis, Conservatoire national des arts et metiers - CNAM, 2008. http://tel.archives-ouvertes.fr/tel-00367626.
Частини книг з теми "Contraintes de cardinalité":
Roussel, Olivier, and Vasco Manquinho. "Chapter 28. Pseudo-Boolean and Cardinality Constraints." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia201012.