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/** \page MethodsDoc Optimization Methods 

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

\section Unconstrained Unconstrained Optimization Methods

<ol type="A">
	<LI>No Derivative Information or Noisy Function Evaluations
<UL>
    <LI> <a href ="classOPTPP_1_1OptPDS.html"> Parallel Direct Search (PDS) Method </a>
    <LI> <a href ="classOPTPP_1_1OptGSS.html"> Generating Set Search (GSS) Method </a>
</UL>

<Li> Derivative Information Available
<UL>
    <LI> <a href ="classOPTPP_1_1OptCGLike.html"> Conjugate Gradient Method </a>
    <LI> <a href ="classOPTPP_1_1OptLBFGSLike.html"> Limited-Memory BFGS Method</a>
    <LI> <a href ="classOPTPP_1_1OptNewtonLike.html"> Newton's Method </a>
</UL>
</OL>

\section Bound_Constraints Bound-Constrained Optimization Methods 
<UL>
    <LI> <a href ="classOPTPP_1_1OptBaNewton.html"> Barrier Newton Method </a>
    <LI> <a href ="classOPTPP_1_1OptBCEllipsoid.html"> Bound Constrained Ellipsoid 
	    Method</a>
    <LI> <a href ="classOPTPP_1_1OptBCNewtonLike.html"> Bound Constrained Newton</a>
    <LI> <a href ="classOPTPP_1_1OptNIPSLike.html"> Nonlinear Interior-Point Method</a>
    <LI> <a href ="classOPTPP_1_1OptNPSOL.html"> NPSOL wrapper </a>
    <LI> <a href ="classOPTPP_1_1OptPDS.html"> Parallel Direct Search (PDS) Method </a>
</UL>


\section GeneralConstraints Generally Constrained Optimization Methods
<UL>
    <LI> <a href ="classOPTPP_1_1OptNIPSLike.html"> Nonlinear Interior-Point Method</a>
    <LI> <a href ="classOPTPP_1_1OptNPSOL.html"> NPSOL wrapper </a>
</UL>

\section LeastSquares Optimization Methods using Gauss-Newton approximations 
<UL>
    <LI> <a href ="classOPTPP_1_1OptDHNIPS.html"> Disaggregated Hessian Nonlinear Interior-Point Method</a>
    <LI> <a href ="classOPTPP_1_1OptNewtonLike.html"> Newton's method </a>
</UL>

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*/