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BBPH: Using progressive hedging within branch and bound to solve multi-stage stochastic mixed integer programs
Authors:Jason Barnett  Jean-Paul Watson  David L. Woodruff
Affiliation:1. Department of Applied Mathematics, University of California Davis, Davis, CA 95616-8609, USA;2. Discrete Math and Optimization Department, Sandia National Laboratories, Albuquerque, NM 87185, USA;3. Graduate School of Management, University of California Davis, Davis, CA 95616-8609, USA
Abstract:Progressive hedging, though an effective heuristic for solving stochastic mixed integer programs (SMIPs), is not guaranteed to converge in this case. Here, we describe BBPH, a branch and bound algorithm that uses PH at each node in the search tree such that, given sufficient time, it will always converge to a globally optimal solution. In addition to providing a theoretically convergent “wrapper” for PH applied to SMIPs, computational results demonstrate that for some difficult problem instances branch and bound can find improved solutions after exploring only a few nodes.
Keywords:Stochastic programming  Progressive hedging  Branch and bound
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