Mapping the convergence of genetic algorithms.
Méthodes de simulation en programmation dynamique stochastique
Methods for solving stochastic bilinear fractional max-min problems
Modular production line optimization: The exPLOre architecture.
Multistage multivariate nested distance: An empirical analysis
Multistage stochastic optimization requires the definition and the generation of a discrete stochastic tree that represents the evolution of the uncertain parameters in time and space. The dimension of the tree is the result of a trade-off between the adaptability to the original probability distribution and the computational tractability. Moreover, the discrete approximation of a continuous random variable is not unique. The concept of the best discrete approximation has been widely explored and...
Multistage stochastic programs: The state-of-the-art and selected bibliography
Multistage stochastic programs via autoregressive sequences and individual probability constraints
The paper deals with a special case of multistage stochastic programming problems. In particular, the paper deals with multistage stochastic programs in which a random element follows an autoregressive sequence and constraint sets correspond to the individual probability constraints. The aim is to investigate a stability (considered with respect to a probability measures space) and empirical estimates. To achieve new results the Wasserstein metric determined by norm and results of multiobjective...