Improving nonlinear programming support in JuMP
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.
