feat: loadBalance() constraint collector #841
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@Christopher-Chianelli For you to review. |
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docs/src/modules/ROOT/pages/constraints-and-score/load-balancing-and-fairness.adoc
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| import java.util.Map; | ||
| import java.util.Objects; | ||
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| public final class LoadBalanceCalculator implements ObjectCalculator<Object, BigDecimal> { |
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So, if I am reading this correctly, this does sqrt(sum(count^2))?
This has the consequence that a "fair" schedule result increases as the number of shifts increases:
Assume two employees, and a perfectly fair schedule, a perfectly fair schedule that is off by one, and a completely unfair schedule. Then these will be the score impact of fairness:
- 2 shifts: fair:
sqrt(2), slightly unfair:sqrt(4), completely unfair:sqrt(4)= 2 (max difference: 0.585786438) - 4 shifts: fair:
sqrt(8), slightly unfair:sqrt(10), completely unfair:sqrt(16)= 4 (max difference: 1.171572875) - 8 shifts: fair:
sqrt(32), slightly unfair:sqrt(34), completely unfair:sqrt(64)= 8 (max difference: 2.343145751)
This means the "baseline" of a perfectly fair schedule increases, and the maximum difference in score increases linearly with the number of shifts.
An alternative formula is "Root of squared deviation from the mean":
sqrt(sum((count - average count)^2)).
For the same dataset:
- 2 shifts: fair: 0, slightly unfair:
sqrt(2), completely unfair:sqrt(2)(max difference: sqrt(2) = 1.414213562) - 4 shifts: fair: 0, slightly unfair:
sqrt(2), completely unfair:sqrt(8)(max difference: sqrt(8) = 2.828427125) - 8 shifts: fair: 0, slightly unfair:
sqrt(2), completely unfair:sqrt(32)(max difference: sqrt(32) = 5.656854249)
the baseline remains the same, although the max difference still scales linearly.
| private BigDecimal result = null; | ||
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| @Override | ||
| public void insert(Object o) { |
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How does this handle "load balance by minutes worked"?
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Closing this PR and will bring a re-thought approach. |
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