Mapping the convergence of genetic algorithms.
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Méthodes de simulation en programmation dynamique stochastique
J. P. Quadrat, M. Viot (1973)
ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique
Methods for solving stochastic bilinear fractional max-min problems
Stephan Tigan, I. M. Stancu-Minasian (1996)
RAIRO - Operations Research - Recherche Opérationnelle
Modular production line optimization: The exPLOre architecture.
Spinellis, Diomidis D., Papadopoulos, Chrissoleon T. (2001)
Mathematical Problems in Engineering
Multistage multivariate nested distance: An empirical analysis
Sebastiano Vitali (2018)
Kybernetika
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
Jitka Dupačová (1995)
Kybernetika
Multistage stochastic programs via autoregressive sequences and individual probability constraints
Vlasta Kaňková (2008)
Kybernetika
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...
Currently displaying 1 – 7 of 7
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