Parallel PIPS-SBB: multi-level parallelism for stochastic mixed-integer programs

DOI10.1007/s10589-019-00074-0zbMath1422.90030OpenAlexW2788091193WikidataQ128410476 ScholiaQ128410476MaRDI QIDQ2419558

Yuji Shinano, Lluís-Miquel Munguía, Deepak Rajan, Geoffrey M. Oxberry

Publication date: 13 June 2019

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://www.osti.gov/biblio/1635781

zbMATH Keywords

parallel algorithmsMIPsparallel branch and boundstochastic MIPs

Mathematics Subject Classification ID

Mixed integer programming (90C11) Stochastic programming (90C15)

Related Items (2)

Asynchronous Lagrangian scenario decomposition ⋮ Linearization and parallelization schemes for convex mixed-integer nonlinear optimization

Uses Software

• ALPS
• SCIP
• UG
• CPLEX
• PySP
• DSP
• MPI/MPICH
• ParaSCIP
• BiCePS
• CHiPPS
• SIPLIB
• PEBBL
• ParaLEX
• GitHub

Cites Work

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• Branching rules revisited
• Could we use a million cores to solve an integer program?
• Faster MIP solutions via new node selection rules
• PySP: modeling and solving stochastic programs in Python
• Parallel distributed-memory simplex for large-scale stochastic LP problems
• On parallelizing dual decomposition in stochastic integer programming
• A stochastic programming approach for supply chain network design under uncertainty
• The million-variable ``march for stochastic combinatorial optimization
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• Computational Experience with a Software Framework for Parallel Integer Programming
• An Automatic Method of Solving Discrete Programming Problems
• Presolve Reductions in Mixed Integer Programming
• 50 Years of Integer Programming 1958-2008
• Preprocessing and Probing Techniques for Mixed Integer Programming Problems
• A Computational Study of Search Strategies for Mixed Integer Programming
• FiberSCIP—A Shared Memory Parallelization of SCIP
• Applications of Stochastic Programming

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