better explanation of objectives

scheduling.tex

@@ -173,18 +173,20 @@ Combining all assessments so that schedules can be compared is the topic of \cre
 
 \paragraph{Objectives}
 We call the result of a quality function an \emph{objective}.
-This is a general concept that tries to cover quality assessments of different units.
+This is a general concept with which we try to handle quality assessments of different units.
+
 Some objectives are better when they are maximized, some are better when they are minimized.
-An objective is therefore a number together with a label \emph{maximize} or \emph{minimize} which indicates how to optimize the objective.
+An objective is therefore a number together with a tag \emph{maximize} or \emph{minimize} which indicates how to compare two objectives of this type.
 Quality functions are not the only source of objectives in a C2 scheduling problem.
 Another objective is the makespan, which is the overall time from the start of the work to the end.
 The makespan should be minimized.
 
 Every problem instance brings its own quality function.
-To evaluate a solution, the quality function is applied to every skill that is assigned a resource.
-For example, the solutions in \cref{fig:SARSchedules} belong to an instance where nine skills must be assigned.
+To evaluate a schedule, the quality function is applied to every capability requirement that has a resource assigned to it.
+This results in a vector of objectives.
+For example, the schedules in \cref{fig:SARSchedules} belong to an instance where nine capability requirements must be assigned.
 These assignments are called the \emph{decision vector} of a solution, because the scheduler must make nine assignment decisions.
-The quality function is applied to nine skill/resource pairs.
+The quality function is applied to nine capability requirement/resource pairs.
 Together with the makespan, every decision vector gives rise to a total of ten objectives, which is called the \emph{objective vector}.
 The goal of the scheduler is to find a decision vector that has a good objective vector.
 The difficulties of comparing objective vectors are described in \cref{sec:mcdm}.