Evolutionary Strategy for Political Districting Problem Using Genetic Algorithm

The aim of the Political Districting Problem is to partition a zone into electoral districts with constraints such as contiguity, population equality, etc. By using statistical physics methods, the problem can be mapped onto a q-state Potts model system, and the political constraints are written as an energy function with interactions between sites or external fields acting on the system. This problem is then transformed into an optimization problem. In this paper, we apply the genetic algorithm to Political Districting Problem. We will illustrate the evolutionary strategy for GA and compare with results from other optimization algorithms.