A new interpretation of the progressive hedging algorithm for multistage stochastic minimization problems - Sun, Jie; Xu, Honglei; Zhang, Min (AMER INST MATHEMATICAL SCIENCES-AIMS, 2020)
The progressive hedging algorithm of Rockafellar and Wets for multistage stochastic programming problems could be viewed as a two-block alternating direction method of multipliers. This correspondence brings in some useful results. In particular, it provides a new proof for the convergence of the progressive hedging algorithm with a flexibility in the selection of primal and dual step lengths and it helps to develop a new progressive hedging algorithm for solving risk averse stochastic optimization problems with cross constraints.