The political districting problem is to study how to partition a comparatively large zone into many minor electoral districts In our previously works we have mapped this political problem onto a q-state Potts model system by using statistical physics methods The political constraints (such as contiguity population equality etc) are transformed to an energy function with interactions between sites or external fields acting on the system Several optimization algorithms such as simulated annealing method and genetic algorithm have been applied to this problem In this report we will show how to apply the Knowledge-based Evolution Algorithm (KEA) to the problem Our test objects include two real cities (Taipei and Kaohsiung) and the simulated cities The results showed the KEA can reach the same minimum which has been found by using other methods in each test case (C) 2010 Elsevier B V All rights reserved
