Parallel Algebraic Modeling for Stochastic Optimization

Abstract

We 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 boiler-plate. StochJuMP allows efficient parallel model instantiation across nodes and efficient data localization. Computational results are presented showing that the model construction is efficient, requiring roughly 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.