SNOW.jl

Optimization framework for nonlinear, gradient-based constrained, sparse optimization problems.
Author byuflowlab
Popularity
26 Stars
Updated Last
10 Months Ago
Started In
January 2021

Sparse Nonlinear Optimization Wrapper (SNOW)

Dev Build Status

The problems we typically solve in our group are nonconvex, nonlinear, constrained, gradient-based, often computationally expensive, and sometimes have sparse Jacobians. This package wraps derivative computation methods and optimization solvers that are well-suited to these types of problems.

Features:

  • Allows easy switching between SNOPT and IPOPT from a common interface passing through all solver options, preserving output in files, and allowing warm starts (for SNOPT).
  • Easy switching between various differentiation methods: ForwardDiff, ReverseDiff, Zygote, FiniteDiff (forward, central, complex step), and user-defined derivatives.
  • Derivative calculations are all non-allocating during optimization.
  • Outputs are also cached as applicable to avoid unnecessary function calls.
  • Methods are provided to help determine sparsity patterns, sparse Jacobians can be updated efficiently with SparseDiffTools (using graph coloring), and the sparsity structure is passed to the solvers.

To Install

] add SNOW