15.4. Continuous Planning (Windowed Planning)

Continuous planning is the technique of planning one or more upcoming planning windows at the same time and repeating that process monthly, weekly, daily or hourly. Because time is infinite, there are infinite future windows, so planning all future windows is impossible. Instead, plan only a fixed number of upcoming planning windows.
Past planning windows are immutable. The first upcoming planning window is considered stable (unlikely to change), while later upcoming planning windows are considered draft (likely to change during the next planning effort). Distant future planning windows are not planned at all.
Past planning windows have only immovable planning entities: the planning entities can no longer be changed (they are unable to move), but some of them are still needed in the score calculation, as they might affect some of the score constraints that apply on the upcoming planning entities. For example: when an employee should not work more than 5 days in a row, he shouldn't work today and tomorrow if he worked the past 4 days already.
Sometimes some planning entities are semi-immovable: they can be changed, but occur a certain score penalty if they differ from their original place. For example: avoid rescheduling hospital beds less than 2 days before the patient arrives (unless it's really worth it), avoid changing the airplane gate during the 2 hours before boarding (unless there is no alternative), ...
Notice the difference between the original planning of November 1th and the new planning of November 5th: some problem facts (F, H, I, J, K) changed, which results in unrelated planning entities (G) changing too.

15.4.1. Immovable Planning Entities

To make some planning entities immovable, simply add an entity SelectionFilter that returns true if an entity is movable and false if it is immovable. 
public class MovableShiftAssignmentSelectionFilter implements SelectionFilter<ShiftAssignment> {

    public boolean accept(ScoreDirector scoreDirector, ShiftAssignment shiftAssignment) {
        ShiftDate shiftDate = shiftAssignment.getShift().getShiftDate();
        NurseRoster nurseRoster = (NurseRoster) scoreDirector.getWorkingSolution();
        return nurseRoster.getNurseRosterInfo().isInPlanningWindow(shiftDate);
    }

}
And configure it like this: 
@PlanningEntity(movableEntitySelectionFilter = MovableShiftAssignmentSelectionFilter.class)
public class ShiftAssignment {
    ...
}
Warning
Custom MoveListFactory and MoveIteratorFactory implementations must make sure that they don't move immovable entities.

15.4.2. Nonvolatile Replanning to minimize disruption (Semi-movable Planning Entities)

Replanning an existing plan can be very disruptive on the plan. If the plan affects humans (such as employees, drivers, ...), very disruptive changes are often undesirable. In such cases, nonvolatile replanning helps: the gain of changing a plan must be higher than the disruption it causes.
For example, in the Machine Reassignment example, the entity has both the planning variable machine and its original value originalMachine: 
@PlanningEntity(...)
public class ProcessAssignment {

    private MrProcess process;
    private Machine originalMachine;
    private Machine machine;

    public Machine getOriginalMachine() {...}

    @PlanningVariable(...)
    public Machine getMachine() {...}

    public boolean isMoved() {
        return originalMachine != null && originalMachine != machine;
    }

    ...
}
During planning, the planning variable machine changes. By comparing it with the originalMachine, a change in plan can be penalized: 
rule "processMoved"
    when
        ProcessAssignment(moved == true)
    then
        scoreHolder.addSoftConstraintMatch(kcontext, -1000);
end
The soft penalty of -1000 means that a better solution is only accepted if it improves the soft score for at least 1000 points per variable changed (or if it improves the hard score).