An Asynchronous Bundle-Trust-Region Method for Dual Decomposition of Stochastic Mixed-Integer Programming
- Argonne National Lab. (ANL), Lemont, IL (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Univ. of Wisconsin-Madison, Madison, WI (United States)
We present an asynchronous bundle-trust-region algorithm within the context of Lagrangian dual decomposition for stochastic mixed-integer programs. The approach solves the Lagrangian master problem by using a bundle method with a trust-region constraint. This scheme enables asynchronous computations and can thus help mitigate severe load imbalance issues (associated with the solution of scenario subproblems) and improve parallel efficiency. We provide a convergence analysis and an implementation of the proposed scheme. We also present extensive numerical results on eighty instances of a large-scale stochastic unit commitment problem, and demonstrate that the proposed approach provides significant reductions in solution time and achieves strong scaling.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES)
- Grant/Contract Number:
- AC52-07NA27344; AC02-06CH11357
- OSTI ID:
- 1497321
- Alternate ID(s):
- OSTI ID: 1510481
- Report Number(s):
- LLNL-JRNL-738242; 890992
- Journal Information:
- SIAM Journal on Optimization, Vol. 29, Issue 1; ISSN 1052-6234
- Publisher:
- SIAMCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Asynchronous level bundle methods
|
journal | July 2019 |
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