Improving nonlinear programming support in JuMP

07/28/2022, 4:30 PM — 5:00 PM UTC
JuMP

Abstract:

In JuMP 1.0, support for nonlinear programming is a second-class citizen. You must use the separate @NL macros, the automatic differentiation engine is a JuMP-specific implementation that cannot be swapped for alternative implementations, and vector-valued nonlinear expressions are not supported. In this talk, we discuss our plans and progress to address these issues and make nonlinear programming a first-class citizen. This work is supported by funding from Los Alamos National Laboratory.

Platinum sponsors

Julia ComputingRelational AIJulius Technology

Gold sponsors

IntelAWS

Silver sponsors

Invenia LabsBeacon BiosignalsMetalenzASMLG-ResearchConningPumas AIQuEra Computing Inc.Jeffrey Sarnoff

Media partners

Packt PublicationGather TownVercel

Community partners

Data UmbrellaWiMLDS

Fiscal Sponsor

NumFOCUS