Parallel Algebraic Modeling for Stochastic Optimization

TitleParallel Algebraic Modeling for Stochastic Optimization
Publication TypeConference Proceedings
Year of Publication2014
AuthorsHuchette, J, Lubin, M, Petra, CG
Conference NameHPTCDL '14
Date Published11/2014
Conference LocationNew Orleans, LA
Other NumbersANL/MCS-P5181-0814
AbstractWe present scalable algebraic modeling software, StochJuMP, for stochastic optimization as applied to power grid economic dispatch. It enables the user to express the problem in a high-level algebraic format with minimal boilerplate. StochJuMP allows efficient parallel model instantiation across nodes and efficient data localization. Computational results are presented showing that the model construction is efficient, requiring less than one percent of solve time. StochJuMP is configured with the parallel interior-point solver PIPS-IPM but is sufficiently generic to allow straight forward adaptation to other solvers.