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claude-codescience

Babysitter nonlinear-optimization-solver

Solve general nonlinear optimization problems

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/mathematics/skills/nonlinear-optimization-solver" ~/.claude/skills/a5c-ai-babysitter-nonlinear-optimization-solver && rm -rf "$T"
manifest: library/specializations/domains/science/mathematics/skills/nonlinear-optimization-solver/SKILL.md
tags
#mathematics#optimization#scientific-computing#constraint-handling#gradient-based
source content

Nonlinear Optimization Solver

Purpose

Provides capabilities for solving general nonlinear optimization problems including constrained and unconstrained formulations.

Capabilities

  • Gradient-based methods (BFGS, L-BFGS, CG)
  • Newton and quasi-Newton methods
  • Interior point methods
  • Sequential quadratic programming (SQP)
  • Global optimization (basin-hopping, differential evolution)
  • Constraint handling

Usage Guidelines

  1. Starting Point: Provide good initial guesses
  2. Gradient Information: Supply gradients when available
  3. Global vs Local: Choose global methods for multimodal problems
  4. Constraint Handling: Use appropriate constraint formulations

Tools/Libraries

  • IPOPT
  • KNITRO
  • NLopt
  • scipy.optimize