Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1142322 | Operations Research Letters | 2013 | 7 Pages |
Abstract
For stochastic mixed-integer programs, we revisit the dual decomposition algorithm of Carøe 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.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Discrete Mathematics and Combinatorics
Authors
Miles Lubin, Kipp Martin, Cosmin G. Petra, Burhaneddin Sandıkçı,