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DFP

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Data Fit Problems (DFP)

$\mathbf {\sum_{k=0}^{K} \|f(x, X_k)-Y_k\| ^2 \to min}$

subjected to

$\mathbf{lb} \le \mathbf{x} \le \mathbf{ub}$

$\mathbf{A x} \le \mathbf{b}$

$\mathbf{A}_\mathbf{eq} \mathbf{x} = \mathbf{b}_\mathbf{eq}$

$\mathbf{\forall i=0,...,I: c_i(x) \le 0}$

$\mathbf{\forall j=0,...,J: h_j(x) = 0}$

$\mathbf{f, c_i, h_j :R^n \to R}$

$\mathbf{x \in R^n,\ X_k \in R^m, Y_k \in R^s}$

OpenOpt DFP examples:

DFP solvers connected to OpenOpt

Solver	License	Made by	Info
converter to nlp	BSD	Dmitrey	Example: r = p.solve('nlp:ralg'). Can handle only smooth functions. See NLP page for list of available NLP solvers

Retrieved from "http://openopt.org/DFP"