Journal Article10.2139/SSRN.2165991
On Parallelizing Dual Decomposition in Stochastic Integer Programming
64
TL;DR: The dual decomposition algorithm of Caroe and Schultz is revisited from a computational perspective and an important bottleneck of parallel execution is addressed by identifying a formulation that permits the parallel solution of the master program by using structure-exploiting interior-point solvers.
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Abstract: For stochastic mixed-integer programs, we revisit the dual decomposition algorithm of Caroe 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.
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