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On the implementation of a log-barrier progressive hedging method for multistage stochastic programs. (English) Zbl 1189.65127
Summary: A progressive hedging method incorporated with self-concordant barrier for solving multistage stochastic programs is proposed recently by G. Zhao [Math. Program. 102, No. 1, 1–24 (2005)]. The method relaxes the nonanticipativity constraints by the Lagrangian dual approach and smoothes the Lagrangian dual function by self-concordant barrier functions. The convergence and polynomial-time complexity of the method have been established. Although the analysis is done on stochastic convex programming, the method can be applied to the nonconvex situation.
We discuss some details on the implementation of this method including when to terminate the solution of unconstrained subproblems with special structure and how to perform a line search procedure for a new dual estimate effectively. In particular, the method is used to solve some multistage stochastic nonlinear test problems. The collection of test problems also contains two practical examples from the literature. We report the results of our preliminary numerical experiments. As a comparison, we also solve all test problems by the well-known progressive hedging method.
MSC:
65K05 Numerical mathematical programming methods
90C15 Stochastic programming
Software:
MSLiP
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References:
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