Journal
OPERATIONS RESEARCH LETTERS
Volume 41, Issue 3, Pages 252-258Publisher
ELSEVIER
DOI: 10.1016/j.orl.2013.02.003
Keywords
Stochastic programming; Mixed-integer programming; Column generation; Dual decomposition; Parallel computing; Bundle methods
Categories
Funding
- US Department of Energy [DE-AC02-06CH11357]
- Office of Science of the US Department of Energy [DE-AC02-06CH11357]
- University of Chicago Booth School of Business
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For stochastic mixed-integer programs, we revisit the dual decomposition algorithm of Came and Schultz from a computational perspective with the aim of its parallelization. We address an important bottleneck of parallel execution by identifying a formulation that permits the parallel solution of the master program by using structure-exploiting interior-point solvers. Our results demonstrate the potential for parallel speedup and the importance of regularization (stabilization) in the dual optimization. Load imbalance is identified as a remaining barrier to parallel scalability. (C) 2013 Elsevier B.V. All rights reserved.
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