Mapping the convergence of genetic algorithms.
Mathematical programming via the least-squares method
The least-squares method is used to obtain a stable algorithm for a system of linear inequalities as well as linear and nonlinear programming. For these problems the solution with minimal norm for a system of linear inequalities is found by solving the non-negative least-squares (NNLS) problem. Approximate and exact solutions of these problems are discussed. Attention is mainly paid to finding the initial solution to an LP problem. For this purpose an NNLS problem is formulated, enabling finding...
Maximal flow problem in a network with a variable structure
Maximization of distances of regular polygons on a circle
This paper presents the solution of a basic problem defined by J. Černý which solves a concrete everyday problem in railway and road transport (the problem of optimization of time-tables by some criteria).
Max-separable equations and the set covering
Mesh-independence and preconditioning for solving parabolic control problems with mixed control-state constraints
Optimal control problems for the heat equation with pointwise bilateral control-state constraints are considered. A locally superlinearly convergent numerical solution algorithm is proposed and its mesh independence is established. Further, for the efficient numerical solution reduced space and Schur complement based preconditioners are proposed which take into account the active and inactive set structure of the problem. The paper ends by numerical tests illustrating our theoretical findings and...
Mesh-independence and preconditioning for solving parabolic control problems with mixed control-state constraints
Optimal control problems for the heat equation with pointwise bilateral control-state constraints are considered. A locally superlinearly convergent numerical solution algorithm is proposed and its mesh independence is established. Further, for the efficient numerical solution reduced space and Schur complement based preconditioners are proposed which take into account the active and inactive set structure of the problem. The paper ends by numerical tests illustrating our theoretical findings and comparing...
Méthodes de résolution du problème de transport et de production d'une entreprise à établissements multiples en présence de coûts fixes
Méthodes de simulation en programmation dynamique stochastique
Méthodes du second ordre dans les problèmes d'optimisation avec contraintes
Méthodes numériques pour la décomposition et la minimisation de fonctions non differentiates.
Métodos duales y algoritmos híbridos para problemas de "set partitioning".
En este artículo estudiamos la utilización de métodos duales en el diseño de algoritmos híbridos para la resolución de problemas de "Set Partitioning" (SP). Las técnicas duales resultan de gran interés para resolver problemas con estructura combinatoria no sólo porque generan cotas inferiores sino porque, además, su utilización junto con heurísticas y procedimientos de generación de desigualdades en el diseño de algoritmos híbridos permite evaluar la calidad de las cotas superiores obtenidas. Los...
Minimisation d'une fonction convexe séparable avec contraintes de rapport entre les variables
Minimización global de un polinomio en la recta real.
En este artículo presentamos y probamos numéricamente un nuevo algoritmo para la minimización global de un polinomio de grado par. El algoritmo está basado en la simple idea de trasladar verticalmente el grafo del polinomio hasta que el eje OX sea tangente al grafo del polinomio trasladado. En esta privilegiada posición, cualquier raíz real del polinomio trasladado es un mínimo global del polinomio original.
Minimization of a convex quadratic function subject to separable conical constraints in granular dynamics
The numerical solution of granular dynamics problems with Coulomb friction leads to the problem of minimizing a convex quadratic function with semidefinite Hessian subject to a separable conical constraints. In this paper, we are interested in the numerical solution of this problem. We suggest a modification of an active-set optimal quadratic programming algorithm. The number of projection steps is decreased by using a projected Barzilai-Borwein method. In the numerical experiment, we compare our...
Minimization of Extended Quadratic Functions.
Mise à jour de la métrique dans les méthodes de quasi-Newton réduites en optimisation avec contraintes d'égalité
Modélisation et optimisation numérique pour la reconstruction d'un polyèdre à partir de son image gaussienne généralisée
Modifications of the limited-memory BFGS method based on the idea of conjugate directions
Simple modifications of the limited-memory BFGS method (L-BFGS) for large scale unconstrained optimization are considered, which consist in corrections of the used difference vectors (derived from the idea of conjugate directions), utilizing information from the preceding iteration. For quadratic objective functions, the improvement of convergence is the best one in some sense and all stored difference vectors are conjugate for unit stepsizes. The algorithm is globally convergent for convex sufficiently...
Multiple objective optimization of hydro-thermal systems using Ritz's method.