@techreport{iiasa4204,
           month = {February},
            type = {IIASA Working Paper},
           title = {On Augmented Lagrangian Decomposition Methods For Multistage Stochastic Programs},
         address = {IIASA, Laxenburg, Austria},
       publisher = {WP-94-005},
            year = {1994},
             url = {https://pure.iiasa.ac.at/id/eprint/4204/},
        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 or decomposing it into nodes  corresponding to stages. In both cases the method has favorable convergence  properties and a structure which makes it convenient for parallel computing  environments.},
          author = {Ruszczynski, A.}
}