Iteration 1 Summary
Business Context: A pharmaceutical company is optimizing the allocation of research resources to study interactions between medicines and enzymes. The objective is to maximize the potential impact of research by prioritizing interactions that are most likely to lead to significant medical advancements, within budget and resource constraints.
Optimization Problem: The company needs to decide which medicine-enzyme interactions to prioritize for research, given a limited budget and resource constraints. The objective is to maximize the expected impact of the research, which is estimated based on historical data and expert opinions.
Objective: maximize sum(impact_coefficients.coefficient[i] * medicine_enzyme_interaction.selected[i]) for all interactions i
Tables Created: 3
Tables Modified: 1
Tables Deleted: 0
Key Change: Schema changes include creating new tables for impact coefficients, costs, and resource usage, and updating business configuration logic for budget and total resources.
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 research costs, resource usage, and expected impacts in pharmaceutical research, ensuring a balance between high-impact and low-cost interactions.