I have an objective to evenly distribute tasks among employees using Timefold Solver.

I have come across two approaches that seem to address this goal:

1. SelectionSorterWeightFactory

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   <code>int leftEmployeeWorkedHours = scoreDirector.computeConstraintWeight(

   "Employee worked hours",

   ConstraintCollectors.sum(shiftAssignment -> shiftAssignment.getEmployee().equals(leftShiftAssignment.getEmployee()) ? shiftAssignment.getDuration() : 0)

   );

   int rightEmployeeWorkedHours = scoreDirector.computeConstraintWeight(

   "Employee worked hours",

   ConstraintCollectors.sum(shiftAssignment -> shiftAssignment.getEmployee().equals(rightShiftAssignment.getEmployee()) ? shiftAssignment.getDuration() : 0)

   );

   // Compare the total worked hours to achieve load balancing

   return Integer.compare(leftEmployeeWorkedHours, rightEmployeeWorkedHours);

   </code>

   <code>int leftEmployeeWorkedHours = scoreDirector.computeConstraintWeight( "Employee worked hours", ConstraintCollectors.sum(shiftAssignment -> shiftAssignment.getEmployee().equals(leftShiftAssignment.getEmployee()) ? shiftAssignment.getDuration() : 0) ); int rightEmployeeWorkedHours = scoreDirector.computeConstraintWeight( "Employee worked hours", ConstraintCollectors.sum(shiftAssignment -> shiftAssignment.getEmployee().equals(rightShiftAssignment.getEmployee()) ? shiftAssignment.getDuration() : 0) ); // Compare the total worked hours to achieve load balancing return Integer.compare(leftEmployeeWorkedHours, rightEmployeeWorkedHours); </code>

   int leftEmployeeWorkedHours = scoreDirector.computeConstraintWeight(
        "Employee worked hours",
        ConstraintCollectors.sum(shiftAssignment -> shiftAssignment.getEmployee().equals(leftShiftAssignment.getEmployee()) ? shiftAssignment.getDuration() : 0)
    );
    int rightEmployeeWorkedHours = scoreDirector.computeConstraintWeight(
        "Employee worked hours",
        ConstraintCollectors.sum(shiftAssignment -> shiftAssignment.getEmployee().equals(rightShiftAssignment.getEmployee()) ? shiftAssignment.getDuration() : 0)
    );
   
    // Compare the total worked hours to achieve load balancing
    return Integer.compare(leftEmployeeWorkedHours, rightEmployeeWorkedHours);
   

2. Another option is to use Constraint like this

[referred from https://docs.timefold.ai/timefold-solver/latest/constraints-and-score/load-balancing-and-fairness ]

   Constraint fairAssignments(ConstraintFactory constraintFactory) {
    return constraintFactory.forEach(ShiftAssignment.class)
            .groupBy(ConstraintCollectors.loadBalance(ShiftAssignment::getEmployee))
            .penalizeBigDecimal(HardSoftBigDecimalScore.ONE_SOFT, LoadBalance::unfairness)
            .asConstraint("fairAssignments");}

My understanding is that if the goal is to influence the selection process, such as balancing workloads or prioritizing preferred options, then the SelectionSorterWeightFactory approach may be more suitable. On the other hand, the Constraint Factory approach is better suited for driving resource limitations and business rules.

However, I would like to get more clarity on the following:

1. When should I choose one approach over the other, or should I use a
   combination of both?

2. What are the key differences between the two approaches, and how do
   they influence the solver’s decision-making process?

3. Can you provide any additional insights or guidelines on how to
   choose the appropriate approach for my use case?

Your clarification on these aspects would be greatly appreciated. Thank you for your time and assistance.