Optimization Methods

This section contains recommendations for optimization algorithms based on problem characteristics.

Unconstrained Optimization Methods

1. No Derivative Information or Noisy Function Evaluations
   • Parallel Direct Search (PDS) Method
   • Generating Set Search (GSS) Method

2. Derivative Information Available
   • Conjugate Gradient Method
   • Limited-Memory BFGS Method
   • Newton's Method

Bound-Constrained Optimization Methods

• Barrier Newton Method
• Bound Constrained Ellipsoid Method
• Bound Constrained Newton
• Nonlinear Interior-Point Method
• NPSOL wrapper
• Parallel Direct Search (PDS) Method

Generally Constrained Optimization Methods

• Nonlinear Interior-Point Method
• NPSOL wrapper

Optimization Methods using Gauss-Newton approximations

• Disaggregated Hessian Nonlinear Interior-Point Method
• Newton's method

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