Adds an a-posteriori decision step to the jiggly example. After NSGA-III
produces the Pareto front, we apply a weighted-sum score over each
objective normalized to [0, 1] across the front (best→1, worst→0,
direction-aware), and report the top three plus a clear recommendation.
The weights are stated explicitly with rationale, not buried in code:
work_fail 45% — screen sleeping mid-meeting is the worst failure
lunch_sleep 30% — the actual design goal
presses 15% — UX friction the user feels
after_hours 10% — minor, mostly screen burn
This is the standard structure for picking a single answer out of a
Pareto set without losing the front itself: someone with different
weights can read the front and pick differently, but we surface a
specific recommendation with reasoning rather than leaving the user
to stare at 84 incomparable rows. Identical normalization could be
swapped for TOPSIS or knee-point detection later if useful.
swaits
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