Iteration 1 Summary
Business Context: A cinema chain aims to maximize its revenue by optimizing the scheduling of films across its cinemas, considering constraints such as cinema capacity, show times per day, and film popularity.
Optimization Problem: Maximize the total revenue generated from film showings across all cinemas. The decision variables are the number of showings per film per cinema per day. Constraints include cinema capacity, maximum show times per day per cinema, and ensuring that each film is shown at least once.
Objective: maximize ∑(Price × Show_times_per_day × Cinema_Capacity)
Tables Created: 0
Tables Modified: 0
Tables Deleted: 0
Key Change: Schema changes include adding tables for missing constraints and updating configuration logic to handle scalar parameters and formulas. Business configuration logic now includes maximum show times and total capacity per day.
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 industry standards, typical cinema operations, and ensuring the optimization problem remains solvable. Cinema capacities and show times were aligned with real-world scenarios, while prices were set to reflect average ticket costs.