Comparing the Similarity of Ohio’s Congressional Districts using the Genetic Algorithm
Start Date
29-4-2022 3:20 PM
Location
Alter Hall 205
Abstract
Gerrymandered districts come from manipulating boundaries in favor of a specific party. To prevent gerrymandering, algorithmic methods have been created in order determine unbiased optimized districts. In this project, the districts are determined by an overall score based on equal population, competitiveness, compactness, and fairness. The focal point of this project used a genetic algorithm, involving an elite collection of maps and evolving them over generations to create the best map. To ensure if the generations of maps improved, the collection of optimized maps were compared to each to calculate a similarity score. This score shows how the determined districts has been improved over time.
Comparing the Similarity of Ohio’s Congressional Districts using the Genetic Algorithm
Alter Hall 205
Gerrymandered districts come from manipulating boundaries in favor of a specific party. To prevent gerrymandering, algorithmic methods have been created in order determine unbiased optimized districts. In this project, the districts are determined by an overall score based on equal population, competitiveness, compactness, and fairness. The focal point of this project used a genetic algorithm, involving an elite collection of maps and evolving them over generations to create the best map. To ensure if the generations of maps improved, the collection of optimized maps were compared to each to calculate a similarity score. This score shows how the determined districts has been improved over time.
