PIPSSBB: A Parallel DistributedMemory BranchandBound Algorithm for Stochastic MixedInteger Programs
Abstract
Stochastic mixedinteger programs (SMIPs) deal with optimization under uncertainty at many levels of the decisionmaking process. When solved as extensive formulation mixed integer programs, problem instances can exceed available memory on a single workstation. In order to overcome this limitation, we present PIPSSBB: a distributedmemory parallel stochastic MIP solver that takes advantage of parallelism at multiple levels of the optimization process. We also show promising results on the SIPLIB benchmark by combining methods known for accelerating Branch and Bound (B&B) methods with new ideas that leverage the structure of SMIPs. Finally, we expect the performance of PIPSSBB to improve further as more functionality is added in the future.
 Authors:

 Georgia Inst. of Technology, Atlanta, GA (United States)
 Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
 Publication Date:
 Research Org.:
 Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
 Sponsoring Org.:
 USDOE
 OSTI Identifier:
 1321445
 Report Number(s):
 LLNLJRNL678917
 Grant/Contract Number:
 AC5207NA27344
 Resource Type:
 Accepted Manuscript
 Journal Name:
 Parallel and Distributed Processing Symposium Workshops, 2016 IEEE International
 Additional Journal Information:
 Conference: 2016 International Parallel and Distributed Processing Symposium (IPDPS) Workshops, 2327 May 2016
 Publisher:
 IEEE
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; twostage stochastic mixedinteger programming; distributed memory algorithm; branch and bound; dual blockangular
Citation Formats
Munguia, LluisMiquel, Oxberry, Geoffrey, and Rajan, Deepak. PIPSSBB: A Parallel DistributedMemory BranchandBound Algorithm for Stochastic MixedInteger Programs. United States: N. p., 2016.
Web. doi:10.1109/IPDPSW.2016.159.
Munguia, LluisMiquel, Oxberry, Geoffrey, & Rajan, Deepak. PIPSSBB: A Parallel DistributedMemory BranchandBound Algorithm for Stochastic MixedInteger Programs. United States. doi:10.1109/IPDPSW.2016.159.
Munguia, LluisMiquel, Oxberry, Geoffrey, and Rajan, Deepak. Sun .
"PIPSSBB: A Parallel DistributedMemory BranchandBound Algorithm for Stochastic MixedInteger Programs". United States. doi:10.1109/IPDPSW.2016.159. https://www.osti.gov/servlets/purl/1321445.
@article{osti_1321445,
title = {PIPSSBB: A Parallel DistributedMemory BranchandBound Algorithm for Stochastic MixedInteger Programs},
author = {Munguia, LluisMiquel and Oxberry, Geoffrey and Rajan, Deepak},
abstractNote = {Stochastic mixedinteger programs (SMIPs) deal with optimization under uncertainty at many levels of the decisionmaking process. When solved as extensive formulation mixed integer programs, problem instances can exceed available memory on a single workstation. In order to overcome this limitation, we present PIPSSBB: a distributedmemory parallel stochastic MIP solver that takes advantage of parallelism at multiple levels of the optimization process. We also show promising results on the SIPLIB benchmark by combining methods known for accelerating Branch and Bound (B&B) methods with new ideas that leverage the structure of SMIPs. Finally, we expect the performance of PIPSSBB to improve further as more functionality is added in the future.},
doi = {10.1109/IPDPSW.2016.159},
journal = {Parallel and Distributed Processing Symposium Workshops, 2016 IEEE International},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {5}
}