XVII th Conference on Stochastic Programming

Large-Scale Experimentation and Analysis of HPC-Based Scenario Decomposition via Progressive Hedging with mpi-sppy

29 juil. 2025, 11:15

30m

F201

Invited talk Stochastic Mixed-Integer Programming Stochastic integer programming

Orateur

Jean-Paul Watson (Lawrence Livermore National Laboratory)

Description

Parallel implementations of scenario-based decomposition strategies are now scalable to thousands and millions of scenarios, thanks to advances in modeling systems (e.g.., Pyomo) and supporting meta-solvers (e.g., mpi-sppy). We describe challenges and their solution considering a large-scale power grid capacity expansion model, where scenarios represent individual days of weather. We discuss in detail various algorithmic tuning and approaches to rapidly finding high-quality solutions to these stochastic programs, utilizing the mpi-sppy meta-solver library.