Document Type

Closed Project

Publication Date

Spring 2012


Robert Dryden

Course Title

Engineering and Technology Management Synthesis

Course Number

ETM 590


Operations research, Apportionment (Election law) -- Oregon -- Mathematical models


Redistricting is the process that local government uses census data to redraw electoral districts lines and boundaries with the purpose to achieve equity of eligible voter population and to eliminate political gerrymandering in order to guarantee fairness in district regard to the one-man one-vote principle. Thus, redistricting should represent everyone voice in district. Since redistricting is considered as important process to guarantee fairness among people in district, many researcher pay attention to develop model system to help redistricting. The model proposed in this paper originates with the purpose to enhance redistricting model of State of Oregon. Since State of Oregon still manually do redistricting, several issues and limitations are presented. Manually redistricting can consider just only one criterion at once, while multiple criterions are needed to optimize the model. Our mathematical model system using operation research with involves more than one criterion, and it is adaptable to be used for other states, not just only for Oregon Metro area. Four criterions involve in the model are as follows: 1) population: with the goal to make each district has equal voter population; 2) age: with the goal to have each district have equal size of eligible voter; 3) income level: with the goal to have people in the same area have the same level of income, and 4) ethnicity: with the goal to group people in district by their ethnicity. The model weight criterion population the most, then age and household income. The model also considers Black people, Asian people, and Hispanic people as criterions by ethnicity. The model is illustrated on 2010 Census Data of Oregon, which include the entire Portland region. As a result, the model has three contributions: 1) Lower computational complexity; 2) Overcoming the complexity of distance definition; and 3) Few constraints. Our result comes up with 10 districts instead of 6 districts stated in map proposed by Oregon metro council.


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