On parallelizing dual decomposition in stochastic integer programming

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 th...

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Veröffentlicht in:Operations research letters Jg. 41; H. 3; S. 252 - 258
Hauptverfasser: Lubin, Miles, Martin, Kipp, Petra, Cosmin G., Sandıkçı, Burhaneddin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.05.2013
Elsevier
Schlagworte:
Bundle methods
Column generation
Computation
Decomposition
Dual decomposition
Integer programming
Mixed-integer programming
Operations research
Optimization
Parallel computing
Parallel processing
Solvers
Stochastic programming
Stochasticity
Dual decomposition
Column generation
Parallel computing
Bundle methods
Mixed-integer programming
Stochastic programming
ISSN:0167-6377, 1872-7468
Online-Zugang:Volltext
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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.
AbstractList 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.
For stochastic mixed-integer programs, we revisit the dual decomposition algorithm of CarA,e 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.
Author Lubin, Miles
Sandıkçı, Burhaneddin
Martin, Kipp
Petra, Cosmin G.
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  surname: Lubin
  fullname: Lubin, Miles
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  organization: Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
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  givenname: Kipp
  surname: Martin
  fullname: Martin, Kipp
  email: kmartin@chicagobooth.edu
  organization: University of Chicago Booth School of Business, Chicago, IL, USA
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  givenname: Cosmin G.
  surname: Petra
  fullname: Petra, Cosmin G.
  email: petra@mcs.anl.gov
  organization: Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, USA
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  givenname: Burhaneddin
  surname: Sandıkçı
  fullname: Sandıkçı, Burhaneddin
  email: burhan@chicagobooth.edu
  organization: University of Chicago Booth School of Business, Chicago, IL, USA
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Issue 3
Keywords Dual decomposition
Column generation
Parallel computing
Bundle methods
Mixed-integer programming
Stochastic programming
Language English
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Snippet For stochastic mixed-integer programs, we revisit the dual decomposition algorithm of Carøe and Schultz from a computational perspective with the aim of its...
For stochastic mixed-integer programs, we revisit the dual decomposition algorithm of CarA,e and Schultz from a computational perspective with the aim of its...
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SubjectTerms Bundle methods
Column generation
Computation
Decomposition
Dual decomposition
Integer programming
Mixed-integer programming
Operations research
Optimization
Parallel computing
Parallel processing
Solvers
Stochastic programming
Stochasticity
Title On parallelizing dual decomposition in stochastic integer programming
URI https://dx.doi.org/10.1016/j.orl.2013.02.003
http://www.econis.eu/PPNSET?PPN=750049448
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