Iteration 3 Summary
Business Context: A university aims to optimize scholarship allocation to students based on academic performance, sports participation, and gaming habits to maximize overall student satisfaction and performance while adhering to budget and participation constraints.
Optimization Problem: Maximize the total weighted sum of student satisfaction, which is influenced by academic performance, sports participation, and gaming habits, subject to budget limits, minimum and maximum hours for sports and gaming, and ensuring students with higher academic performance receive more scholarships.
Objective: maximize ∑(w1 * GPA[i] + w2 * HoursPerWeek[i] + w3 * Hours_Played[i])
Tables Created: 0
Tables Modified: 0
Tables Deleted: 0
Key Change: Schema changes include adding missing optimization requirements to business configuration logic and ensuring all mappings are complete.
Status: Complete
Confidence: high
Next Focus: Ready for convergence
Mapping Adequacy: mostly_good
Business Configuration Parameters: 2

Triple Expert Data: Values were determined based on realistic university scholarship allocation scenarios, considering typical GPA ranges, sports and gaming participation hours, and budget constraints.