@techreport{iiasa4089,
           month = {December},
            type = {IIASA Working Paper},
           title = {On Augmented Lagrangian Decomposition Methods for Multistage Stochastic Programs},
         address = {IIASA, Laxenburg, Austria},
       publisher = {WP-94-125},
            year = {1994},
             url = {https://pure.iiasa.ac.at/id/eprint/4089/},
        abstract = {A general decomposition framework for large convex optimization problems based on augmented Lagrangians is described. The approach is then applied to multistage stochastic programming problems in two different ways: by decomposing the problem into scenarios and by decomposing it into nodes corresponding to stages. Theoretical convergence properties of the two approaches are derived and a computational illustration is presented.},
          author = {Rosa, C. H. and Ruszczynski, A.}
}