Iteration 1 Summary
Business Context: A music streaming platform aims to optimize its storage and bandwidth usage by selecting a subset of songs to store locally on servers, minimizing the total file size while ensuring a diverse and high-quality music library.
Optimization Problem: Minimize the total file size of songs stored locally, subject to constraints on the minimum number of songs per genre, the minimum average rating of songs, and the maximum number of songs per artist.
Objective: minimize ∑(file_size_i × x_i), where x_i is a binary decision variable indicating whether song i is stored locally.
Tables Created: 2
Tables Modified: 1
Tables Deleted: 0
Key Change: Schema changes include creating new tables for decision variables and constraints, moving scalar parameters to business_configuration_logic.json, and updating the data dictionary to reflect optimization mappings.
Status: Complete
Confidence: high
Next Focus: Ready for convergence
Mapping Adequacy: mostly_good
Business Configuration Parameters: 4

Triple Expert Data: Values were determined based on realistic scenarios for a music streaming platform, considering typical file sizes, song ratings, and genre/artist distributions. Parameters were set to ensure a diverse and high-quality library while optimizing storage.