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Political Districting: from classical models to recent approaches

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  • Federica Ricca
  • Andrea Scozzari
  • Bruno Simeone

Abstract

The Political Districting problem has been studied since the 60’s and many different models and techniques have been proposed with the aim of preventing districts’ manipulation which may favor some specific political party (gerrymandering). A variety of Political Districting models and procedures was provided in the Operations Research literature, based on single- or multiple-objective optimization. Starting from the forerunning papers published in the 60’s, this article reviews some selected optimization models and algorithms for Political Districting which gave rise to the main lines of research on this topic in the Operations Research literature of the last five decades. Copyright Springer Science+Business Media New York 2013

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  • 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.
    • Handle: RePEc:spr:annopr:v:204:y:2013:i:1:p:271-299:10.1007/s10479-012-1267-2
    DOI: 10.1007/s10479-012-1267-2
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    Cited by:

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    5. Yin Xia & Dianfeng Liu & Yaolin Liu & Jianhua He & Xiaofeng Hong, 2014. "Alternative Zoning Scenarios for Regional Sustainable Land Use Controls in China: A Knowledge-Based Multiobjective Optimisation Model," IJERPH, MDPI, vol. 11(9), pages 1-28, August.
    6. Diglio, Antonio & Peiró, Juanjo & Piccolo, Carmela & Saldanha-da-Gama, Francisco, 2021. "Solutions for districting problems with chance-constrained balancing requirements," Omega, Elsevier, vol. 103(C).
    7. 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.
    8. Diglio, Antonio & Peiró, Juanjo & Piccolo, Carmela & Saldanha-da-Gama, Francisco, 2023. "Approximation schemes for districting problems with probabilistic constraints," European Journal of Operational Research, Elsevier, vol. 307(1), pages 233-248.
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    10. Benadè, Gerdus & Ho-Nguyen, Nam & Hooker, J.N., 2022. "Political districting without geography," Operations Research Perspectives, Elsevier, vol. 9(C).
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    14. Yao, Ming-Jong & Lin, Jen-Yen & Lin, Yu-Liang & Fang, Shu-Cherng, 2020. "An integrated algorithm for solving multi-customer joint replenishment problem with districting consideration," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    15. 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.
    16. 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).
    17. 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.
    18. Kiera W. Dobbs & Rahul Swamy & Douglas M. King & Ian G. Ludden & Sheldon H. Jacobson, 2024. "An Optimization Case Study in Analyzing Missouri Redistricting," Interfaces, INFORMS, vol. 54(2), pages 162-187, March.
    19. 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.
    20. Ponce, Diego & Puerto, Justo & Temprano, Francisco, 2024. "Mixed-integer linear programming formulations and column generation algorithms for the Minimum Normalized Cuts problem on networks," European Journal of Operational Research, Elsevier, vol. 316(2), pages 519-538.
    21. Ríos-Mercado, Roger Z. & Bard, Jonathan F., 2019. "An exact algorithm for designing optimal districts in the collection of waste electric and electronic equipment through an improved reformulation," European Journal of Operational Research, Elsevier, vol. 276(1), pages 259-271.
    22. Sandoval, M. Gabriela & Álvarez-Miranda, Eduardo & Pereira, Jordi & Ríos-Mercado, Roger Z. & Díaz, Juan A., 2022. "A novel districting design approach for on-time last-mile delivery: An application on an express postal company," Omega, Elsevier, vol. 113(C).

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