Iteration 2 Summary
Business Context: A university aims to optimize the allocation of pet care resources to students based on their pets' needs and the students' demographics. The goal is to minimize the total cost of pet care while ensuring that each pet receives adequate care based on its type, age, and weight, and that the total resources do not exceed the available budget and weight capacity.
Optimization Problem: The optimization problem aims to minimize the total cost of pet care by allocating resources efficiently. The decision variables represent the amount of resources allocated to each pet. Constraints ensure that each pet receives a minimum level of care based on its type, age, and weight, and that the total resources do not exceed the available budget and weight capacity.
Objective: minimize ∑(cost_per_pet_type[PetType] × resource_allocation[PetID])
Tables Created: 1
Tables Modified: 0
Tables Deleted: 0
Key Change: Added resource_allocation table to map decision variables, updated business configuration logic with new scalar parameters, and ensured all mappings align with OR expert's requirements.
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 pet care costs, care requirements, and resource allocation limits, ensuring that the optimization problem remains meaningful and solvable.