IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v287y2020i1d10.1007_s10479-019-03295-y.html
   My bibliography  Save this article

Goal programming approach for political districting in Santa Catarina State: Brazil

Author

Listed:
  • Anderson Kenji Hirose

    (Universidade Federal do Paraná (UFPR))

  • Cassius Tadeu Scarpin

    (Universidade Federal do Paraná (UFPR))

  • José Eduardo Pécora Junior

    (Universidade Federal do Paraná (UFPR)
    la Logistique et le Transport (CIRRELT))

Abstract

In the Brazilian judiciary, the Electoral Registry Offices (EROs) are responsible for managing the Brazilian electoral districts. Moreover, not only do they organize elections in their district, but they are also responsible for managing the registration of electors and supervising the political parties. Brazil has a multi-party system with more than 35 political parties competing over the 295 cities of Santa Catarina state, which had over 4.98 million voters in 2017. In this context, we present a mixed integer model, with the concepts of goal programming and contiguity graph, to propose a more equilibrated distribution of political districts to Santa Catarina state. The mathematical model considers the political districting criteria (population balance, spatial contiguity, and compactness), and also considers the particularities of the Brazilian electoral system (minimum number of voters in an electoral district, maximum electoral zones per city, and so forth). The objective of the problem is to determine the optimum set of districts for the most efficient use of public resources and best service to the population. Therefore, there must be a balance of workload among the (EROs), i.e., a steady number of electors and nominating petitions per district. The solution proposed succeeded in presenting a set of districts with a better workload distribution while respecting all the districting criteria and the Brazilian legislation. Compared to the current situation, the model shows a reduction in the standard deviation of the electorate distribution per district of 7520 voters. The solution obtained by the proposed model for the Brazilian electoral system in the state of Santa Catarina may be used by any other of the 26 Brazilian states. The proposed model is a particularization of the classic political districting problem since it inserts complementary constraints to this classic problem from the operational research literature.

Suggested Citation

  • Anderson Kenji Hirose & Cassius Tadeu Scarpin & José Eduardo Pécora Junior, 2020. "Goal programming approach for political districting in Santa Catarina State: Brazil," Annals of Operations Research, Springer, vol. 287(1), pages 209-232, April.
    • Handle: RePEc:spr:annopr:v:287:y:2020:i:1:d:10.1007_s10479-019-03295-y
    DOI: 10.1007/s10479-019-03295-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-019-03295-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-019-03295-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cinzia Colapinto & Raja Jayaraman & Simone Marsiglio, 2017. "Multi-criteria decision analysis with goal programming in engineering, management and social sciences: a state-of-the art review," Annals of Operations Research, Springer, vol. 251(1), pages 7-40, April.
    2. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    3. Federica Ricca & Andrea Scozzari & Bruno Simeone, 2013. "Political Districting: from classical models to recent approaches," Annals of Operations Research, Springer, vol. 204(1), pages 271-299, April.
    4. Victoriano Ramírez-González & Blanca Delgado-Márquez & Antonio Palomares & Adolfo López-Carmona, 2014. "Evaluation and possible improvements of the Swedish electoral system," Annals of Operations Research, Springer, vol. 215(1), pages 285-307, April.
    5. Zilla Sinuany-Stern & H. Sherman, 2014. "Operations research in the public sector and nonprofit organizations," Annals of Operations Research, Springer, vol. 221(1), pages 1-8, October.
    6. Xin Tang & Ameur Soukhal & Vincent T’kindt, 2014. "Preprocessing for a map sectorization problem by means of mathematical programming," Annals of Operations Research, Springer, vol. 222(1), pages 551-569, November.
    7. Isabella Lari & Friedrich Pukelsheim & Federica Ricca, 2014. "Mathematical modeling of electoral systems: analysis, evaluation, optimization. In memory of Bruno Simeone (1945–2010)," Annals of Operations Research, Springer, vol. 215(1), pages 1-14, April.
    8. Xia, Meimei & Chen, Jian, 2015. "Multi-criteria group decision making based on bilateral agreements," European Journal of Operational Research, Elsevier, vol. 240(3), pages 756-764.
    9. G. Pontuale & F. Dalton & S. Genovese & E. Nave & A. Petri, 2014. "The electoral system for the Italian Senate: an analogy with deterministic chaos?," Annals of Operations Research, Springer, vol. 215(1), pages 245-256, April.
    10. S. W. Hess & J. B. Weaver & H. J. Siegfeldt & J. N. Whelan & P. A. Zitlau, 1965. "Nonpartisan Political Redistricting by Computer," Operations Research, INFORMS, vol. 13(6), pages 998-1006, December.
    11. Banu Lokman & Murat Köksalan & Pekka J. Korhonen & Jyrki Wallenius, 2016. "An interactive algorithm to find the most preferred solution of multi-objective integer programs," Annals of Operations Research, Springer, vol. 245(1), pages 67-95, October.
    12. Meimei Xia & Jian Chen & Juliang Zhang, 2015. "Multi-criteria decision making based on relative measures," Annals of Operations Research, Springer, vol. 229(1), pages 791-811, June.
    13. Johanna Camargo Pérez & Martha Carrillo & Jairo Montoya-Torres, 2015. "Multi-criteria approaches for urban passenger transport systems: a literature review," Annals of Operations Research, Springer, vol. 226(1), pages 69-87, March.
    14. M. Salazar-Aguilar & Roger Ríos-Mercado & José González-Velarde & Julián Molina, 2012. "Multiobjective scatter search for a commercial territory design problem," Annals of Operations Research, Springer, vol. 199(1), pages 343-360, October.
    15. GARFINKEL, Robert S. & NEMHAUSER, Geroge L., 1970. "Optimal political districting by implicit enumeration techniques," LIDAM Reprints CORE 54, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. R. S. Garfinkel & G. L. Nemhauser, 1970. "Optimal Political Districting by Implicit Enumeration Techniques," Management Science, INFORMS, vol. 16(8), pages 495-508, April.
    17. Ricca, Federica & Simeone, Bruno, 2008. "Local search algorithms for political districting," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1409-1426, September.
    18. Na Chen & Zeshui Xu & Meimei Xia, 2015. "The ELECTRE I Multi-Criteria Decision-Making Method Based on Hesitant Fuzzy Sets," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 621-657.
    19. Anuj Mehrotra & Ellis L. Johnson & George L. Nemhauser, 1998. "An Optimization Based Heuristic for Political Districting," Management Science, INFORMS, vol. 44(8), pages 1100-1114, August.
    20. Patricia Jaramillo & Ricardo Smith & JoaquÍn Andréu, 2005. "Multi-Decision-Makers Equalizer: A Multiobjective Decision Support System for Multiple Decision-Makers," Annals of Operations Research, Springer, vol. 138(1), pages 97-111, September.
    21. James Cochran & David Curry & Rajesh Radhakrishnan & Jon Pinnell, 2014. "Political engineering: optimizing a U.S. Presidential candidate’s platform," Annals of Operations Research, Springer, vol. 215(1), pages 63-87, April.
    22. Fernando Tavares-Pereira & José Figueira & Vincent Mousseau & Bernard Roy, 2007. "Multiple criteria districting problems," Annals of Operations Research, Springer, vol. 154(1), pages 69-92, October.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Eiselt, H.A. & Marianov, Vladimir, 2020. "Maximizing political vote in multiple districts," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sebastián Moreno & Jordi Pereira & Wilfredo Yushimito, 2020. "A hybrid K-means and integer programming method for commercial territory design: a case study in meat distribution," Annals of Operations Research, Springer, vol. 286(1), pages 87-117, March.
    2. Swamy, Rahul & King, Douglas M. & Ludden, Ian G. & Dobbs, Kiera W. & Jacobson, Sheldon H., 2024. "A practical optimization framework for political redistricting: A case study in Arizona," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    3. Djordje Dugošija & Aleksandar Savić & Zoran Maksimović, 2020. "A new integer linear programming formulation for the problem of political districting," Annals of Operations Research, Springer, vol. 288(1), pages 247-263, May.
    4. Eduardo Álvarez-Miranda & Camilo Campos-Valdés & Maurcio Morales Quiroga & Matías Moreno-Faguett & Jordi Pereira, 2020. "A Multi-Criteria Pen for Drawing Fair Districts: When Democratic and Demographic Fairness Matter," Mathematics, MDPI, vol. 8(9), pages 1-26, August.
    5. Balázs Fleiner & Balázs Nagy & Attila Tasnádi, 2017. "Optimal partisan districting on planar geographies," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(4), pages 879-888, December.
    6. Federica Ricca & Andrea Scozzari & Bruno Simeone, 2013. "Political Districting: from classical models to recent approaches," Annals of Operations Research, Springer, vol. 204(1), pages 271-299, April.
    7. Christian Haas & Lee Hachadoorian & Steven O Kimbrough & Peter Miller & Frederic Murphy, 2020. "Seed-Fill-Shift-Repair: A redistricting heuristic for civic deliberation," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-34, September.
    8. Baghersad, Milad & Emadikhiav, Mohsen & Huang, C. Derrick & Behara, Ravi S., 2023. "Modularity maximization to design contiguous policy zones for pandemic response," European Journal of Operational Research, Elsevier, vol. 304(1), pages 99-112.
    9. Rui Fragoso & Conceição Rego & Vladimir Bushenkov, 2016. "Clustering of Territorial Areas: A Multi-Criteria Districting Problem," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(2), pages 179-198, December.
    10. Xin Tang & Ameur Soukhal & Vincent T’kindt, 2014. "Preprocessing for a map sectorization problem by means of mathematical programming," Annals of Operations Research, Springer, vol. 222(1), pages 551-569, November.
    11. F Caro & T Shirabe & M Guignard & A Weintraub, 2004. "School redistricting: embedding GIS tools with integer programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 836-849, August.
    12. Juan Carlos Duque & Raúl Ramos & Jordi Suriñach, 2007. "Supervised Regionalization Methods: A Survey," International Regional Science Review, , vol. 30(3), pages 195-220, July.
    13. Benadè, Gerdus & Ho-Nguyen, Nam & Hooker, J.N., 2022. "Political districting without geography," Operations Research Perspectives, Elsevier, vol. 9(C).
    14. Antonio Diglio & Stefan Nickel & Francisco Saldanha-da-Gama, 2020. "Towards a stochastic programming modeling framework for districting," Annals of Operations Research, Springer, vol. 292(1), pages 249-285, September.
    15. Hyun Kim & Yongwan Chun & Kamyoung Kim, 2015. "Delimitation of Functional Regions Using a p-Regions Problem Approach," International Regional Science Review, , vol. 38(3), pages 235-263, July.
    16. Han, Jialin & Hu, Yaoguang & Mao, Mingsong & Wan, Shuping, 2020. "A multi-objective districting problem applied to agricultural machinery maintenance service network," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1120-1130.
    17. Oded Berman & Zvi Drezner & Arie Tamir & George Wesolowsky, 2009. "Optimal location with equitable loads," Annals of Operations Research, Springer, vol. 167(1), pages 307-325, March.
    18. Maria da Conceição Rego & Rui Fragoso & Vladimir Bushenkov, 2014. "Clustering of Territorial Areas: A Multi-Criteria Districting Problem," ERSA conference papers ersa14p218, European Regional Science Association.
    19. Sommer Gentry & Eric Chow & Allan Massie & Dorry Segev, 2015. "Gerrymandering for Justice: Redistricting U.S. Liver Allocation," Interfaces, INFORMS, vol. 45(5), pages 462-480, October.
    20. Tammy Drezner & Zvi Drezner, 2011. "A note on equity across groups in facility location," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(7), pages 705-711, October.

    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:spr:annopr:v:287:y:2020:i:1:d:10.1007_s10479-019-03295-y. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.