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Districting Using a TSP-Based Genetic Algorithm

机译:采用基于TSP的遗传算法区分

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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.
机译:由于政党和特殊利益集团试图将各国分为有利于其候选人的地区,在美国立法机构的国会区的绘制创造了大量争议。本文提出的遗传算法试图找到一套大约相同的人口的紧凑型和连续的国会区。该遗传算法利用基于编码和遗传运算符的技术,用于解决旅行推销员问题(TSP)。这种在地区人口平等附近的编码力量,并使用健身功能来促进地区脱节性和紧凑性。后期处理步骤进一步炼制地区人口平等。使用2000年人口普查数据为三个州(北卡罗来纳州,南卡罗来纳州和爱荷华州)提供了结果。

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