Thanks to their inherent properties, probabilistic graphical models are one of the prime
candidates for machine learning and decision making tasks especially in uncertain domains …

Estimation of distribution algorithm (EDA) is an efficient population-based stochastic search
technique. Since it was proposed, many attempts have been made to improve its …

The use of copula-based models in EDAs (estimation of distribution algorithms) is currently
an active area of research. In this context, the copulaedas package for R provides a platform …

In this paper, a new Estimation of Distribution Algorithm (EDA) is presented. The proposed
algorithm employs a dependency tree as a graphical model and bivariate copula functions …

Four undirected graphical models based on copula theory are investigated in relation to
their use within an estimation of distribution algorithm (EDA) to address the molecular …

Designing a power plant is a complex process that requires consideration of multiple
optimization criteria, such as safety, environmental impact, and efficiency. This paper …

The two-stage flow-shop scheduling problem investigated in this work aims minimize the
resource consumption of non-identical job sizes. The flow shop consists of two batch …

Resumen Este Trabajo de Fin de Máster se centra en la exploración y aplicación los
Algoritmos de Estimación de Distribuciones (EDAs), con el propósito de modelizar …

Estimation of distribution algorithms based on copula functions Page 1 Estimation of
Distribution Algorithms based on Copula Functions Rogelio Salinas-Gutiérrez ∗ …

In this work a mathematical model for evolutionary optimization is proposed. It takes
advantages of the good properties of copula-vines to overcome many of the limitations of …