Powell Optima
PowellOptima ( LineSearch * ls, int iter , double tol , double changOf, double delta, int vebose) a constructor
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PowellOptima ( LineSearch * ls, int iter , double tol , double changeOf, double delta) a constructor | |||||||||||||
Model <double> | optimizer ( Model <double>& m0) Powell's search starting from m0, returns an optimum model | ||||||||||||
Model <long> | optimizer ( Model <long>& m0) Powell's search starting from m0, returns an optimum model | ||||||||||||
const char* | className () const |
Powell's method can be considered a derivative-free version of the conjugate gradient algorithm (Powell, M., Computer Journal, 7, 155-162). Here the objective function is minimized from an initial model along a set of conjugate directiions generatied by the procedure without resorting to the gradient of the objective function.Although an interesting algorithm, Powell's method has demonstrated to have a high computational cost, due the excessive number of line search required to compute the conjugate directions (see Applied Nonlinear Programming, by David Himmelblau for details. It seems that the standard conjugate gradient by Hesteness and Stiefel with numerical derivatives is a more efficient procedure.
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