Ir arriba
Información del artículo

Clustering algorithms for scenario tree generation: Application to natural hydro inflows

J.M. Latorre, S. Cerisola, A. Ramos

In stochastic optimization problems, uncertainty is normally represented by means of a scenario tree. Finding an accurate representation of this uncertainty when dealing with a set of historical series is an important issue, because of its influence in the results of the above mentioned problems. This article uses a procedure to create the scenario tree divided into two phases: the first one produces a tree that represents accurately the original probability distribution, and in the second phase that tree is reduced to make it tractable. Several clustering methods are analysed and proposed in the paper to obtain the scenario tree. Specifically, these are applied to an academic case and to natural hydro inflows series, and comparisons amongst them are established according to these results.

Palabras clave: Scenario tree generation; Uncertainty modelling; Stochastic programming

European Journal of Operational Research. Volumen: 181 Numero: 3 Páginas: 1339-1353

Índice de impacto JCR y cuartil Scopus: 1.096 (2007); 3.428 - Q1 (2017).

Referencia DOI: DOI icon 10.1016/j.ejor.2005.11.045    

Publicado en papel: Septiembre 2007.

    Líneas de investigación:
  • *Planificación táctica a medio plazo

pdf  Previsualizar
pdf Solicitar el artículo completo a los autores

Aviso legal  |  Política de cookies |  Política de Privacidad

© Universidad Pontificia Comillas, Escuela Técnica Superior de Ingeniería - ICAI, Instituto de Investigación Tecnológica

Calle de Santa Cruz de Marcenado, 26 - 28015 Madrid, España - Tel: (+34) 91 5422 800