首页> 外文会议>Computational Science - ICCS 2007 pt.4; Lecture Notes in Computer Science; 4490 >Evolutionary Strategy for Political Districting Problem Using Genetic Algorithm
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Evolutionary Strategy for Political Districting Problem Using Genetic Algorithm

机译:遗传算法的政治分区问题演化策略

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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.
机译:政治分区问题的目的是将一个区域划分为具有连续性,人口平等等约束条件的选举区。通过使用统计物理方法,可以将该问题映射到一个q状态的Potts模型系统中,并且可以将政治约束条件映射到被写为具有作用在系统上的站点或外部场之间的相互作用的能量函数。然后将此问题转换为优化问题。本文将遗传算法应用于政治区划问题。我们将说明遗传算法的进化策略,并与其他优化算法的结果进行比较。

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