Iteration 1 Summary
Business Context: A high school aims to maximize student happiness by pairing them as friends based on mutual likes, ensuring each student has a balanced number of friends within specified limits.
Optimization Problem: Maximize the total happiness score by pairing students as friends, subject to constraints on the minimum and maximum number of friends per student and ensuring mutual friendships.
Objective: maximize ∑(happiness_score[student_id, friend_id] * x[student_id, friend_id])
Tables Created: 1
Tables Modified: 1
Tables Deleted: 0
Key Change: Schema changes include creating a HappinessScore table to map likes between students, and moving max_friends and min_friends to business_configuration_logic.json. The Friend table is modified to ensure mutual friendships.
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 high school scenarios, ensuring each student has a balanced number of friends and mutual likes are represented. The happiness scores reflect mutual interests, and the number of friends per student adheres to the configured constraints.