Models for Global Constraint Applications - Cork Constraint ...

3.3.2 Frozen Schedule
The scheduling system is not just used to create one master schedule, but is
constantly re-run to update the schedule with the latest production data, so
that the effects of delays on customer deliveries are immediately visible. When
rescheduling we do not want the system to re-arrange the schedule completely.
In the user interface we have the possibility to “freeze” the schedule of a line
up to a given task. This fixes the order of the tasks, but not their start times,
as these might be affected by the work in progress. This “freezing” can also be
used to protect manual changes in the schedule.
3.3.3 Task Ordering
If we have multiple tasks producing the same product, then we can order them
according to their due date. This reduces the amount of bin capacity we will
need for this product and cuts some part of the search tree.
3.3.4 Throughput Learning
∀i,j∈I : ri = rj ∧ duei < duej =⇒ si < sj
(36)
The accuracy of the schedule depends to a large extend on the accuracy of the
throughput data which controls the duration of tasks and to some extend the
machine assignment. The system contains a learning module which periodically
checks actual production data in order to recalculate the throughput data for
each product. The user can interact with this module by excluding certain
measurements or by forcing a particular value.
3.4 Search
In a problem like this where there are many different types of variables with domains
which even initially are very different in size it is not possible to rely on a
standard labelling routine which selects the variables without an understanding
of their purpose in the model.
We have developed a number of strategies which interleave the assignment
of successor and setup variables, but which also use the start or end variables
for task selection.
a This is a standard labelling routine, which was not able to find any solution
for the sample problems below. It was therefore not included in the result
tables.
b This strategy first assigns for each selected task the setup and then the successor
variable. The selection is done by the most constrained successor
variable. Doing this for all tasks fixes the machine assignment and the
sequence of tasks on each machine. At the end it labels the start of all
tasks to the earliest time point.
c Like b, but select the task with the smallest value in the successor variable.
d Like b, but select the task with the most constrained setup variable first.
19