Iteration 2 Summary
Business Context: A music ensemble aims to optimize the number of pieces performed by each member across various performances to maximize overall attendance, while ensuring fair distribution of pieces among members and respecting performance capacity constraints.
Optimization Problem: Maximize the total attendance across all performances by optimizing the number of pieces each member performs, subject to constraints on the maximum number of pieces a member can perform, the total number of pieces per performance, and ensuring each member is assigned at least one piece.
Objective: maximize ∑(Attendance_j × ∑(x_ij)) where x_ij is the number of pieces member i performs in performance j
Tables Created: 1
Tables Modified: 0
Tables Deleted: 0
Key Change: Added attendance_data table to capture attendance per performance, updated business configuration logic with attendance-related scalar parameters, and ensured all mappings align with OR expert requirements.
Status: Complete
Confidence: high
Next Focus: Ready for convergence
Mapping Adequacy: mostly_good
Business Configuration Parameters: 1

Triple Expert Data: Values were determined based on realistic scenarios for a music ensemble, considering typical attendance numbers, member capabilities, and performance constraints. The data ensures a balanced distribution of pieces among members and performances, while respecting the optimization constraints.