IDEAS home Printed from https://ideas.repec.org/a/igg/jagr00/v8y2017i4p1-18.html
   My bibliography  Save this article

Contiguity-Based Optimization Models for Political Redistricting Problems

Author

Listed:
  • Myung Kim

    (Department of Science and Policy, Gyeonggido Business & Science Accelerator(GBSA), Suwon, South Korea)

  • Ningchuan Xiao

    (Department of Geography, The Ohio State University, Columbus, OH, USA)

Abstract

Political redistricting is a process used to redraw political boundaries based on a number of criteria that include population equality, minority representation, contiguity, and compactness. Redistricting plans can be difficult to draw manually and since the 1970s the use of computers in the creation of redistricting plans has increased dramatically. The purpose of this paper is to formulate the problem of finding redistricting plans as optimization problems on the basis of population equality and contiguity. The authors specifically address the problem from the contiguity perspective. They developed two exact optimal models: one based on a minimum spanning tree and one based on network flows. They discuss the spatial representation and the formulation of contiguity for both models and compare the performance of these two models, along with a third model developed in the literature, using a variety of synthetic and real data. The authors' results confirm that such a problem is computationally intensive and more efficient methods are needed for large size problems, but with appropriate formulation approaches they can obtain useful baseline solutions to these problems with relatively small size. They also find that multiple optimal solutions with different spatial configurations may exist for the same problem, which presents a new challenge to the development of solution methods for political redistricting problems.

Suggested Citation

  • Myung Kim & Ningchuan Xiao, 2017. "Contiguity-Based Optimization Models for Political Redistricting Problems," International Journal of Applied Geospatial Research (IJAGR), IGI Global, vol. 8(4), pages 1-18, October.
  • Handle: RePEc:igg:jagr00:v:8:y:2017:i:4:p:1-18
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAGR.2017100101
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shubham Akshat & Sommer E. Gentry & S. Raghavan, 2024. "Heterogeneous donor circles for fair liver transplant allocation," Health Care Management Science, Springer, vol. 27(1), pages 20-45, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jagr00:v:8:y:2017:i:4:p:1-18. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.