Iteration 2 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: 1
Tables Modified: 0
Tables Deleted: 0
Key Change: Schema changes include creating a new table for scholarship amounts, updating the data dictionary, and adding necessary business configuration logic parameters to address missing optimization requirements.
Status: In progress
Confidence: medium
Next Focus: Define and map the decision variable Scholarship_Amount[i] for linear optimization
Mapping Adequacy: mostly_good
Business Configuration Parameters: 0
