public static AllocationResult createEstimatedAllocationResult(Task t, PlanningFactory ldmf) {
Enumeration preferences = t.getPreferences();
if (preferences != null && preferences.hasMoreElements()) {
// do something really simple for now.
Vector aspects = new Vector();
Vector results = new Vector();
while (preferences.hasMoreElements()) {
Preference pref = (Preference) preferences.nextElement();
int at = pref.getAspectType();
aspects.addElement(new Integer(at));
ScoringFunction sf = pref.getScoringFunction();
// allocate as if you can do it at the "Best" point
double myresult = ((AspectScorePoint) sf.getBest()).getValue();
results.addElement(new Double(myresult));
}
int[] aspectarray = new int[aspects.size()];
double[] resultsarray = new double[results.size()];
for (int i = 0; i < aspectarray.length; i++)
aspectarray[i] = (int) ((Integer) aspects.elementAt(i)).intValue();
for (int j = 0; j < resultsarray.length; j++)
resultsarray[j] = (double) ((Double) results.elementAt(j)).doubleValue();
AllocationResult myestimate = ldmf.newAllocationResult(0.0, true, aspectarray, resultsarray);
return myestimate;
}
// if there were no preferences...return a null estimate for the allocation result (for now)
return null;
}
/** This is the driving function in the whole packing process. */
public double execute() {
// boolean finished = false;
double tonsPacked = 0;
if (_gp.getLoggingService().isInfoEnabled())
_gp.getLoggingService().info("Filler.execute - entered.");
int numTasks = 0;
int numParents = 0;
// while there's still ammo to put in milvans
while (_sz.moreTasksInQueue()) {
// initialize the aggregation
ArrayList agglist = new ArrayList();
double amount = 0.0;
double earliest = 0.0;
double latest = java.lang.Double.POSITIVE_INFINITY;
// while our milvan is not yet full and there is more ammo left to pack
while (_ac.getQuantity() - amount > MIN_DELTA && _sz.moreTasksInQueue()) {
// ask the sizer for what an amount that would fill the milvan
Task t = _sz.provide(_ac.getQuantity() - amount, earliest, latest);
if (t == null) { // the next task is outside the earliest->latest window
// finished = true;
break;
}
numTasks++;
// if we reach here, t is a Task that provides
// some amount towards our overall amount
double provided = t.getPreferredValue(AspectType.QUANTITY);
if (_gp.getLoggingService().isInfoEnabled()) {
_gp.getLoggingService()
.info(
"Filler.execute - adding "
+ provided
+ " to agg list vs "
+ (_ac.getQuantity() - amount)
+ " amount "
+ amount);
}
Preference endDatePref = t.getPreference(AspectType.END_TIME);
ScoringFunction sf = endDatePref.getScoringFunction();
AspectScorePoint aspStart = sf.getDefinedRange().getRangeStartPoint();
AspectScorePoint aspBest = sf.getBest();
AspectScorePoint aspEnd = sf.getDefinedRange().getRangeEndPoint();
Date taskEarlyDate = new Date((long) aspStart.getValue());
Date taskBestDateMinusFiveDays =
new Date((long) aspBest.getValue() - MAX_GROUP_DAYS * ONE_DAY_MILLIS);
// no earlier than earliest arrival, but no more than 5 days before best
if (taskBestDateMinusFiveDays.getTime() < taskEarlyDate.getTime())
taskBestDateMinusFiveDays = taskEarlyDate;
if (taskBestDateMinusFiveDays.getTime() > earliest) {
earliest = taskBestDateMinusFiveDays.getTime();
}
// restrict the window of time within which we'll aggregate tasks together
// to be
//
// earliest arrival->best date + one day
//
// instead of
//
// earliest arrival->latest arrival
//
// because that can have problems when we replan
// tasks without plan elements (happens when all aggregations of an mptask get
// removed when any parent is removed). Resulting task has too narrow a time
// window, since the replanned transport task will have an arrival window of
// now->best date, and now could potentially be too close to the best date.
Date taskLateDate = new Date((long) aspEnd.getValue());
Date taskBestDatePlusOneDay = new Date((long) aspBest.getValue() + ONE_DAY_MILLIS);
// no later than late date, but no more than one day after best
if (taskBestDatePlusOneDay.getTime() > taskLateDate.getTime())
taskBestDatePlusOneDay = taskLateDate;
if (taskBestDatePlusOneDay.getTime() < latest) {
latest = taskBestDatePlusOneDay.getTime();
}
amount += provided;
agglist.add(t);
}
if (!agglist.isEmpty()) {
double loadedQuantity = createMPTask(agglist);
numParents += agglist.size();
TRANSPORT_TONS += loadedQuantity;
tonsPacked += loadedQuantity;
}
if (_gp.getLoggingService().isInfoEnabled()) {
_gp.getLoggingService()
.info("Filler.execute - aggregating together " + agglist.size() + " parents:");
for (Iterator iter = agglist.iterator(); iter.hasNext(); ) {
Task task = (Task) iter.next();
_gp.getLoggingService()
.info(
"Filler.execute - "
+ task.getUID()
+ " end date "
+ new Date((long) task.getPreferredValue(AspectType.END_TIME)));
}
}
}
if (numTasks != numParents)
_gp.getLoggingService()
.error(
"Filler.execute - num tasks created "
+ numTasks
+ " != parents of MPTask "
+ numParents);
if (numParents != _sz.sizedMade)
_gp.getLoggingService()
.error(
"Filler.execute - sizer num tasks made "
+ _sz.sizedMade
+ " != total parents of MPTask "
+ numParents);
if (_gp.getLoggingService().isInfoEnabled())
_gp.getLoggingService()
.info("Packer - current aggregated requested transport: " + TRANSPORT_TONS + " tons.");
if (_gp.getLoggingService().isInfoEnabled())
_gp.getLoggingService().info("Filler.execute - exited.");
return tonsPacked;
}