Commit 62b6bee0 authored by Markus Klinik's avatar Markus Klinik

Jan Martin's suggestions; some spacing issues

parent ddc34887
......@@ -95,7 +95,7 @@ The swab deck tasks have no quality function, any crew member is equally suited
The staff meeting needs the commander and the section leaders present, there can be no variation in the assignment, the scheduler just has to find a time slot where all required people are free.
\Cref{fig:realistic-scenario} shows a solution for this scenario.
The important points to observe are as follows.
The important points to note are as follows.
The tasks LoadAmmunition, PrepareWeapon, PreActionCalibration, and UseWeapon all need a weapon that can engage small surface targets, and the same weapon should be assigned to all those tasks.
After all, it does not make sense to load ammunition for a gun but then engage with another one.
In the problem instance this constraint is modelled using resource affinity, and the scheduler only produces solutions where the constraint is satisfied.
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......@@ -163,7 +163,7 @@ This way of schedule building has some of advantages and disadvantages.
It is simple to understand and easy to implement.
An advantage is that it allows modelling task priorities.
Tasks earlier earlier in the instance definition get scheduled first.
Tasks earlier in the instance definition get scheduled first.
Another advantage is that the schedules it builds are valid by construction, where no resource is assigned to two tasks that are overlapping in time, and where tasks are always preceded by their predecessors.
Every valid assignment has at least one valid schedule, and the schedule builder will always find one.
......@@ -187,7 +187,7 @@ The greedy schedule builder processes tasks in the order in which they occur, so
Task 3 could be scheduled at time 0.}
\label{fig:greedy-fails}
\end{figure}
Finding the shortest schedule for a given assignment is an optimization problem on its own, which we leave for future work.
Finding the shortest schedule for a given assignment is itself an optimization problem, which we leave for future work.
\subsection{Quality Functions}
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......@@ -12,8 +12,8 @@ This paper is written for participants of the MAST conference, who have operatio
This article makes the following contributions.
\begin{itemize}[noitemsep]
\item We identify the kind of scheduling problem that arises in C2.
\item We implement a scheduling algorithm solves instances of the identified problem.
\item We demonstrate the capabilities and limitations of our scheduler by means of example scenarios.
\item We implement a scheduling algorithm that solves instances of the identified problem.
\item We demonstrate the features and limitations of our scheduler by means of example scenarios.
\item We perform a literature study to compare our problem with related work.
\end{itemize}
This paper combines known concepts of the fields of project scheduling, multi-criteria optimization and evolutionary algorithms and applies them to a novel variant of the resource-constrained project scheduling problem.
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......@@ -28,7 +28,7 @@ They use a technique called \emph{column generation} to estimate lower bounds an
Finally, they use \emph{recovering beam search} to solve large instances.
One of his supervisors wrote her Ph.D. thesis about solving the MSRCPSP \cite{MorineauN2006, MorineauN2007, Morineau2008}.
\citet{Artigues2008} has written a book about the resource-constrained scheduling problem, which contains a chapter about the multi-skill variant.
\citet{Artigues2008} has written a book about the resource constrained scheduling problem, which contains a chapter about the multi-skill variant.
\citet{CorreiaLS2012} were among the first ones to study solving the multi-skill variant of the RCPSP.
In this publication, they call it RCPSP with flexible resources.
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