Weekly constraint optimizer

Protect the floor.
Build proof above it.

Make paid work and health non-negotiable, then direct the remaining week toward study, personalized demos, and targeted outreach.

activity, track, max, impact, income, fitness, min
Hours allocated-
Income protected-
Fitness protected-
Impact points-
Model waiting0 proof hours0 integer choices

Computed weekly sprint

Load a real activity set to begin.

Every selected and displaced activity will appear here with hours, impact, income, and binding limits.

Decision boundaryImpact points are your declared planning priorities, not hiring probabilities. Wages, health needs, and activity estimates require your review.

Stability and ambition can share one week.

Floors protect the commitments that cannot be traded away for a higher score.

Maximums prevent one attractive activity from swallowing every available hour.

Zero-hour rows reveal the opportunity cost of the schedule, rather than hiding it.

Source constraints and whole-hour allocations

Read the explanation

The saved sample pays eighteen dollars per paid hour. Meeting its two hundred sixteen dollar income floor requires twelve paid hours, exactly the paid shift maximum. Its four fitness hour floor requires four training hours. At twenty pixels per hour, the bars show twelve paid hours and four fitness hours. These are declared planning coefficients and constraints, not guaranteed wages or a fitness prescription. Of the sample thirty hours, twelve paid and four fitness hours leave fourteen hours. The two hour study minimum leaves twelve hours for eight demo and four outreach hours. These bars show eight demo and four outreach hours at twenty pixels per hour. The model uses whole-hour integer choices, maximizes declared impact and respects each activity maximum. Impact weights do not predict hiring or admissions. The sample has six activity rows, including an open source row allocated zero hours. Five allocated rows plus one displaced row still make six exported activities. These bars use sixty pixels per row. The sample impact is twelve paid plus ten study plus seventy two demo plus twenty eight outreach, totaling one hundred twenty two declared points. Export retains inputs, allocations, constraints, versions and limitations. Infeasible input shows an error rather than claiming a new feasible schedule.

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