Summary of Tao Solvers¶
Unconstrained¶
Algorithm 
Associated Type 
Objective 
Gradient 
Hessian 
Constraints 
Jacobian 

NelderMead 
X 

Conjugate Gradient 
X 
X 

Limited Memory Variable Metric (quasiNewton) 
X 
X 

Orthantwise Limited Memory (quasiNewton) 
X 
X 

Bundle Method for Regularized Risk Minimization 
X 
X 

Newton Line Search 
X 
X 
X 

Newton Trust Region 
X 
X 
X 
Bound Constrained¶
Algorithm 
Associated Type 
Objective 
Gradient 
Hessian 
Constraints 
Jacobian 
Constraint Type 

Bounded Conjugate Gradient 
X 
X 
Box constraints 

Bounded Limited Memory Variable Metric (QuasiNewton) 
X 
X 
Box constraints 

Bounded QuasiNewton Line Search 
X 
X 
Box constraints 

Bounded Newton Line Search 
X 
X 
Box constraints 

Bounded Newton TrustRegion 
X 
X 
Box constraints 

Gradient Projection Conjugate Gradient 
X 
X 
Box constraints 

Bounded Quadratic Interior Point 
X 
X 
Box constraints 

Tron 
X 
X 
X 
Box constraints 
Complementarity¶
Algorithm 
Associated Type 
Objective 
Gradient 
Hessian 
Constraints 
Jacobian 
Constraint Type 

ActiveSet Feasible Line Search 
X 
X 
Complementarity 

ActiveSet Infeasible Line Search 
X 
X 
Complementarity 

Semismooth Feasible Line Search 
X 
X 
Complementarity 

Semismooth Infeasible Line Searchx 
X 
X 
Complementarity 
Nonlinear Least Squares¶
Algorithm 
Associated Type 
Objective 
Gradient 
Hessian 
Constraints 
Jacobian 
Constraint Type 

POUNDERS 
X 
Box Constraints 
PDEConstrained¶
Algorithm 
Associated Type 
Objective 
Gradient 
Hessian 
Constraints 
Jacobian 
Constraint Type 

Linearly Constrained Lagrangian 
X 
X 
X 
X 
X 
PDE Constraints 
Constrained¶
Algorithm 
Associated Type 
Objective 
Gradient 
Hessian 
Constraints 
Jacobian 
Constraint Type 

Interior Point Method 
X 
X 
X 
X 
X 
General Constraints 

BarrierBased PrimalDual Interior Point 
X 
X 
X 
X 
X 
General Constraints 