Iteration 1 Summary
Business Context: A university aims to maximize student participation in elections by allocating resources (e.g., campaign materials, reminders) to different majors based on historical voting patterns and student demographics. The optimization model ensures resource allocation respects budget limits, minimum and maximum allocation per major, and proportional allocation based on student numbers.
Optimization Problem: Maximize the total expected votes across all election positions by allocating resources to different majors. The decision variables represent the amount of resources allocated to each major. Constraints include budget limits, minimum and maximum resource allocations per major, and proportional allocation based on the number of students in each major.
Objective: maximize ∑(expected_votes_per_major × resource_allocation_per_major)
Tables Created: 2
Tables Modified: 1
Tables Deleted: 0
Key Change: Schema changes include creating tables for expected votes, resource allocations, and budget constraints. Configuration logic updates include scalar parameters for budget and resource limits, and formulas for expected votes calculation.
Status: Complete
Confidence: high
Next Focus: Ready for convergence
Mapping Adequacy: mostly_good
Business Configuration Parameters: 5

Triple Expert Data: Values were determined based on realistic university demographics, historical voting patterns, and resource allocation practices. The goal was to ensure that the optimization problem is meaningful and solvable while respecting business configuration logic.