Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Redistricting is the process of dividing a geographic area into districts or zones. This process has been considered in the past as a problem that is computationally too complex for an automated system to be developed that can produce unbiased plans.   present a novel method for redistricting a geographic area using a heuristic-based approach for polygonal spatial clustering. While clustering geospatial polygons several complex issues need to be addressed – such as: removing order dependency, clustering all polygons assuming no outliers, and strategically utilizing domain knowledge to guide the clustering process. In order to address these special needs,  have developed the Constrained Polygonal Spatial Clustering (CPSC) algorithm that holistically integrates do-main knowledge in the form of cluster-level and instance-level constraints and uses heuristic functions to grow clusters. In order to illustrate the usefulness of our algorithm  have applied it to the problem of formation of unbiased congressional districts. Furthermore,  compare and contrast our algorithm with two other approaches proposed in the literature for redistricting, namely – graph partitioning and simulated annealing.
['Deepti Joshi', 'Leen-Kiat Soh', 'Ashok Samal']
I am writing a research paper on a idea Redistricting Using Heuristic-Based Polygonal Clustering
[{"from": "human", "value": "I am writing a research paper on a idea Redistricting Using Heuristic-Based Polygonal Clustering"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Redistricting is the process of dividing a geographic area into districts or zones. This process has been considered in the past as a problem that is computationally too complex for an automated system to be developed that can produce unbiased plans.   present a novel method for redistricting a geographic area using a heuristic-based approach for polygonal spatial clustering. While clustering geospatial polygons several complex issues need to be addressed \u2013 such as: removing order dependency, clustering all polygons assuming no outliers, and strategically utilizing domain knowledge to guide the clustering process. In order to address these special needs,  have developed the Constrained Polygonal Spatial Clustering (CPSC) algorithm that holistically integrates do-main knowledge in the form of cluster-level and instance-level constraints and uses heuristic functions to grow clusters. In order to illustrate the usefulness of our algorithm  have applied it to the problem of formation of unbiased congressional districts. Furthermore,  compare and contrast our algorithm with two other approaches proposed in the literature for redistricting, namely \u2013 graph partitioning and simulated annealing."}]