Adapt AMPL part
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@ -85,7 +85,6 @@
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description={},
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}
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\newglossaryentry{gls-chr}{
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name={constraint handling rules},
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description={},
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@ -191,11 +190,6 @@
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description={},
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}
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\newglossaryentry{linear-program}{
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name={linear program},
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description={},
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}
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\newglossaryentry{gls-lcg}{
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name={lazy clause generation},
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description={},
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@ -848,7 +848,6 @@ can then be rewritten as linear \glspl{constraint} using the \glspl{variable}
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\label{line:back-mip-channel} & x_{i} = \sum_{j=1}^{n} j * y_{ij} & \forall_{i=1}^{n} \\
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\label{line:back-mip-row} & \sum_{i=1}^{n} y_{ij} \leq 1 & \forall_{j=1}^{n}
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\end{align}
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% & \sum_{j=1} y_{ij} \leq 1 & \forall_{i=1}^{n}\\
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The encoding of this variable uses only integers. Like the \gls{cp} model,
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@ -963,20 +962,15 @@ expressions and functions provided by the language.
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One of the most used \cmls\ is \gls{ampl} \autocite{fourer-2003-ampl}. As the
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name suggest, \gls{ampl} was designed to allow modellers to express problems
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through the use of mathematical equations. It is therefore also described as an
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``algebraic modelling language''. Specifically an \gls{ampl} model generally
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describes a \gls{linear-program}. In a \gls{linear-program} the \glspl{variable}
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can take any value from a continuous range and the \gls{objective} and
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\glspl{constraint} can only use linear function over \glspl{variable} (\ie\
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\(\sum c_{i} x_{i}\), where all \(c_{i}\) are \glspl{parameter} and all
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\(x_{i}\) are \glspl{variable}).
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Depending on the \gls{solver} targeted by \gls{ampl}, the language can give the
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modeller access to additional functionality. For \glspl{solver} that have a
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\gls{mip} solving method, the modellers can require \glspl{variable} to be
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integers. Different types of \glspl{solver} can also have access to different
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types of constraints, such as quadratic and non-linear constraints. \gls{ampl}
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has even been extended to allow the usage of certain \glspl{global} when using a
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\gls{cp} \gls{solver} \autocite{fourer-2002-amplcp}.
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``algebraic modelling language''. Specifically \gls{ampl} was designed to model
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linear programs. These days \gls{ampl} has been extended to allow more advanced
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\gls{solver} usage. Depending on the \gls{solver} targeted by \gls{ampl}, the
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language can give the modeller access to additional functionality. For
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\glspl{solver} that have a \gls{mip} solving method, the modellers can require
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\glspl{variable} to be integers. Different types of \glspl{solver} can also have
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access to different types of constraints, such as quadratic and non-linear
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constraints. \gls{ampl} has even been extended to allow the usage of certain
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\glspl{global} when using a \gls{cp} \gls{solver} \autocite{fourer-2002-amplcp}.
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\begin{example}
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