Iteration 1 Summary
Business Context: A university aims to optimize the assignment of teachers to courses to maximize the overall grade performance of students. Each teacher has a different impact on the grade performance based on their expertise and experience, and each teacher can only be assigned to one course at a time.
Optimization Problem: The goal is to maximize the total expected grades of all courses by optimally assigning teachers to courses. Each teacher-course assignment has an associated expected grade improvement, and each teacher can only be assigned to one course at a time.
Objective: maximize sum(expected_improvement[Course_ID, Teacher_ID] * assignment[Course_ID, Teacher_ID])
Tables Created: 2
Tables Modified: 1
Tables Deleted: 0
Key Change: Schema changes include creating new tables for decision variables and constraint bounds, modifying existing tables to improve mapping adequacy, and updating business configuration logic for scalar parameters and formulas.
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 typical university settings where teachers have varying impacts on student performance, and courses require specific expertise.