Iteration 1 Summary
Business Context: A university aims to optimize student allocation to restaurants based on preferences and spending habits, maximizing satisfaction while keeping total spending within a predefined budget. Satisfaction is modeled as a linear function of restaurant ratings and time spent.
Optimization Problem: Maximize student satisfaction by allocating students to preferred restaurants, ensuring total spending does not exceed the budget and restaurant capacities are not exceeded. The problem is formulated as a linear optimization model.
Objective: maximize ∑(satisfaction_score[StuID, ResID] * x[StuID, ResID])
Tables Created: 2
Tables Modified: 1
Tables Deleted: 0
Key Change: Schema changes include creating tables for satisfaction scores and restaurant capacities, modifying the Visits_Restaurant table to better map decision variables, and adding business configuration logic for budget and satisfaction score calculation.
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 university restaurant scenarios, considering typical student spending, restaurant capacities, and satisfaction metrics derived from time spent and restaurant ratings.