Iteration 2 Summary
Business Context: A company aims to optimize the allocation of office spaces across multiple buildings to minimize the total leasing cost while ensuring each company's space requirements are met based on their sales and assets.
Optimization Problem: The objective is to minimize the total leasing cost of office spaces across different buildings. The decision variables represent the amount of space allocated to each company in each building. Constraints ensure that each company's space requirements are met, the total space in each building is not exceeded, and the allocation is non-negative.
Objective: minimize ∑(cost_per_sqft[building_id] × space_allocated[building_id, company_id])
Tables Created: 1
Tables Modified: 0
Tables Deleted: 0
Key Change: Added space_allocated table to map decision variables, updated business configuration logic with scalar parameters and formulas, and ensured schema follows normalization principles.
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 business scenarios, considering typical office space costs, company space requirements, and building capacities. Data was generated to ensure a balanced optimization problem with feasible constraints.