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\end{align}
</math>
where <math>\mathbf{x} \in \mathbb{R}^n</math> represents the vector of variables to be determined, <math>\mathbf{c}, \mathbf{d} \in \mathbb{R}^n</math> and <math>\mathbf{b} \in \mathbb{R}^m</math> are vectors of (known) coefficients, <math>A \in \mathbb{R}^{m \times n}</math> is a (known) matrix of coefficients and <math>\alpha, \beta \in \mathbb{R}</math> are constants. The constraints have to restrict the [[feasible region]] to <math>\{\mathbf{x} | \mathbf{d}^T\mathbf{x} + \beta > 0\}</math>, i.e. the region on which the denominator is positive.<ref name="CC">{{cite journal |last1=Charnes |first1=A. |last2=Cooper |first2=W. W. |author2-link=William W. Cooper|title=Programming with Linear Fractional Functionals|journal=Naval Research Logistics Quarterly |volume=9 |year=1962 |pages=
==Transformation to a linear program==
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==Duality==
Let the dual variables associated with the constraints <math>A\mathbf{y} - \mathbf{b} t \leq \mathbf{0}</math> and <math>\mathbf{d}^T \mathbf{y} + \beta t - 1 = 0</math> be denoted by <math>\mathbf{u}</math> and <math>\lambda</math>, respectively. Then the dual of the LFP above is <ref>{{cite journal|last1=Schaible |first1=Siegfried |title=Parameter-free Convex Equivalent and Dual Programs| url=http://www.springerlink.com/content/kv02870752256413/ |journal=Zeitschrift für Operations Research |volume=18 |year=1974 |issue=5 |pages=
:<math>
\begin{align}
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