Congressional Districting Using a TSP-Based Genetic Algorithm

Sean L. Forman^* and Yading Yue

Mathematics and Computer Science Department
Saint Joseph's University
Philadelphia, PA 19131, USA^**

Abstract. The drawing of congressional districts by legislative bodies in the United States creates a great deal of controversy each decade as political parties and special interest groups attempt to divide states into districts beneficial to their candidates. The genetic algorithm presented in this paper attempts to find a set of compact and contiguous congressional districts of approximately equal population. This genetic algorithm utilizes a technique based on an encoding and genetic operators used to solve Traveling Salesman Problems (TSP). This encoding forces near equality of district population and uses the fitness function to promote district contiguity and compactness. A post-processing step further refines district population equality. Results are provided for three states (North Carolina, South Carolina, and Iowa) using 2000 census data.

^*Corresponding author: sean.forman@sju.edu, http://www.sju.edu/~sforman/
^**Special thanks to Alberto Segre for providing support and a sounding board for this work, Saint Joseph's University for support of this work, the U.S. Census Bureau Geography Division for their guidance, and the reviewers for their comments.

LNCS 2724, p. 2072 ff.

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