Large Neighborhood Local Search for the P-Median Problem
Large quadratic programming problems generated by rigid body simulation.
Large-scale nonlinear programming algorithm using projection methods
A method for solving large convex optimization problems is presented. Such problems usually contain a big linear part and only a small or medium nonlinear part. The parts are tackled using two specialized (and thus efficient) external solvers: purely nonlinear and large-scale linear with a quadratic goal function. The decomposition uses an alteration of projection methods. The construction of the method is based on the zigzagging phenomenon and yields a non-asymptotic convergence, not dependent...
Le point sur quelques méthodes directes de recherche de l'extremum d'une fonction monodimensionnelle unimmodale
Le problème de collecte des ordures urbaines
Le problème des signes de Thurstone. Une application de la méthode SEP
Le problème du voyageur de commerce dans un produit cartésien de deux graphes
Le traitement des solutions quasi optimales en programmation linéaire continue : une synthèse
Learnheuristics: hybridizing metaheuristics with machine learning for optimization with dynamic inputs
This paper reviews the existing literature on the combination of metaheuristics with machine learning methods and then introduces the concept of learnheuristics, a novel type of hybrid algorithms. Learnheuristics can be used to solve combinatorial optimization problems with dynamic inputs (COPDIs). In these COPDIs, the problem inputs (elements either located in the objective function or in the constraints set) are not fixed in advance as usual. On the contrary, they might vary in a predictable (non-random)...
Least Squares with a Quadratic Constraint.
Legendre functions and the method of random Bregman projections.
Les effets de l’exposant de la fonction barrière multiplicative dans les méthodes de points intérieurs
Les méthodes de points intérieurs en programmation linéaire connaissent un grand succès depuis l’introduction de l’algorithme de Karmarkar. La convergence de l’algorithme repose sur une fonction potentielle qui, sous sa forme multiplicative, fait apparaître un exposant . Cet exposant est, de façon générale, choisi supérieur au nombre de variables du problème. Nous montrons dans cet article que l’on peut utiliser des valeurs de plus petites que . Ceci permet d’améliorer le conditionnement de...
Les effets de l'exposant de la fonction barrière multiplicative dans les méthodes de points intérieurs
Les méthodes de points intérieurs en programmation linéaire connaissent un grand succès depuis l'introduction de l'algorithme de Karmarkar. La convergence de l'algorithme repose sur une fonction potentielle qui, sous sa forme multiplicative, fait apparaître un exposant p. Cet exposant est, de façon générale, choisi supérieur au nombre de variables n du problème. Nous montrons dans cet article que l'on peut utiliser des valeurs de p plus petites que n. Ceci permet d'améliorer le conditionnement...
L'Espace Vectoriel Pseudo-Booléen Généralisé
Levitin-Polyak well-posedness for equilibrium problems with functional constraints.
Lexicographic and time minimization in the transportation problem
LFS functions in multi-objective programming
We find conditions, in multi-objective convex programming with nonsmooth functions, when the sets of efficient (Pareto) and properly efficient solutions coincide. This occurs, in particular, when all functions have locally flat surfaces (LFS). In the absence of the LFS property the two sets are generally different and the characterizations of efficient solutions assume an asymptotic form for problems with three or more variables. The results are applied to a problem in highway construction, where...
Limit behaviour of trajectories involving subgradients of convex functions
Limit cycle prediction based on evolutionary multiobjective formulation.
Limited memory solution of bound constrained convex quadratic problems arising in video games
We describe the solution of a bound constrained convex quadratic problem with limited memory resources. The problem arises from physical simulations occurring within video games. The motivating problem is outlined, along with a simple interior point approach for its solution. Various linear algebra issues arising in the implementation are explored, including preconditioning, ordering and a number of ways of solving an equivalent augmented system. Alternative approaches are briefly surveyed, ...