Handling CVaR objectives and constraints in two-stage stochastic models

Based on the polyhedral representation of Künzi-Bay and Mayer [Künzi-Bay, A., Mayer, J., 2006. Computational aspects of minimizing conditional value-at-risk. Computational Management Science 3, 3–27] , we propose decomposition frameworks for handling CVaR objectives and constraints in two-stage stoc...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	European journal of operational research 2008-12, Vol.191 (3), p.888-911
1. Verfasser:	FABIAN, Csaba I
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Convex programming Decomposition Decomposition methods Exact sciences and technology Finance Mathematical programming Operational research and scientific management Operational research. Management science Polyhedra Portfolio theory Risk theory. Actuarial science Stochastic models Stochastic programming Studies
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	Based on the polyhedral representation of Künzi-Bay and Mayer [Künzi-Bay, A., Mayer, J., 2006. Computational aspects of minimizing conditional value-at-risk. Computational Management Science 3, 3–27] , we propose decomposition frameworks for handling CVaR objectives and constraints in two-stage stochastic models. For the solution of the decomposed problems we propose special Level-type methods.
ISSN:	0377-2217 1872-6860
DOI:	10.1016/j.ejor.2007.02.052