Move a model in the introduction to after first reference
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@ -50,11 +50,6 @@ And, only one task of the same job can be scheduled at the same time.
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We assume that each job has a task for every machine.
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As an \gls{opt-prb}, our goal is to find a schedule that minimises the finishing time of the last task.
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\begin{listing}
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\pyfile{assets/listing/intro_open_shop.mod}
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\caption{\label{lst:intro-open-shop} An \glsxtrshort{ampl} model of the open shop problem}
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\end{listing}
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\Cref{lst:intro-open-shop} shows an \glsxtrshort{ampl} model for the open shop problem.
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In order of occurence, \lrefrange{line:intro:param:start}{line:intro:param:end} show the declarations of the \prbpars{}.
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To create an \instance{} of the problem, the user provides the number of jobs and machines that are considered, and the duration of each task.
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@ -63,6 +58,11 @@ Additionally, we declare the end time of the last task as a \variable{}, to ease
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This \variable{} is made to be our optimisation goal on \lref{line:intro:goal}.
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Finally, \lrefrange{line:intro:con:start}{line:intro:con:end} express the \constraints{} of our problem in terms of equations bound by logic.
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\begin{listing}
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\pyfile{assets/listing/intro_open_shop.mod}
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\caption{\label{lst:intro-open-shop} An \glsxtrshort{ampl} model of the open shop problem}
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\end{listing}
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The \glsxtrshort{ampl} model provides a clear definition of the problem class, but it can be argued that its meaning is hard to decipher.
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\glsxtrshort{ampl} does not provide any way to capture common concepts, such as one task preceding another or that two tasks cannot overlap in our example.
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Additionally, the process to encode an \instance{} into a \gls{slv-mod} all happens ``behind the scenes''.
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