A Progressive Hedging Based Branch-and-Bound Algorithm for Stochastic Mixed-Integer Programs
نویسندگان
چکیده
Progressive Hedging (PH) is a well-known algorithm for solving multi-stage stochastic convex optimization problems. Most previous extensions of PH for stochastic mixed-integer programs have been implemented without convergence guarantees. In this paper, we present a new framework that shows how PH can be utilized while guaranteeing convergence to globally optimal solutions of stochastic mixed-integer convex programs. We demonstrate the effectiveness of the proposed framework through computational experiments.
منابع مشابه
Integration of progressive hedging and dual decomposition in stochastic integer programs
We present a method for integrating the Progressive Hedging (PH) algorithm and the Dual Decomposition (DD) algorithm of Carøe and Schultz for stochastic mixed-integer programs. Based on the correspondence between lower bounds obtained with PH and DD, a method to transform weights from PH to Lagrange multipliers in DD is found. Fast progress in early iterations of PH speeds up convergence of DD ...
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