Iteration 1 Summary
Business Context: A bodybuilding competition organizer wants to select a team of bodybuilders to maximize the total score based on their Snatch and Clean & Jerk performances, while ensuring the team meets certain diversity and physical criteria. The selection must respect constraints on the total number of bodybuilders, their average height, and their average weight.
Optimization Problem: The goal is to maximize the total score of the selected team, which is the sum of the Snatch and Clean & Jerk scores of the chosen bodybuilders. The selection must respect constraints on the total number of bodybuilders, their average height, and their average weight.
Objective: maximize ∑(Snatch_i + Clean_Jerk_i) * x_i, where x_i is a binary decision variable indicating whether bodybuilder i is selected
Tables Created: 1
Tables Modified: 0
Tables Deleted: 0
Key Change: Schema changes include adding a table for decision variables and updating configuration logic to handle team size constraints and business metrics.
Status: Complete
Confidence: high
Next Focus: Ready for convergence
Mapping Adequacy: mostly_good
Business Configuration Parameters: 3

Triple Expert Data: Values were determined based on typical bodybuilding competition data, ensuring realistic performance scores and physical attributes. The data was generated to respect the constraints and enable a meaningful optimization problem.