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Applying simulated annealing to design compact zones

Author

Listed:
  • Rincón García, Eric Alfredo

    (Universidad Autónoma Metropolitana-Azcapotzalco. Departamento de Sistemas.)

  • Gutiérrez Andrade, Miguel Ángel

    (Universidad Autónoma Metropolitana-Iztapalapa. Departamento de Ingeniería Eléctrica.)

  • Ramírez Rodríguez, Javier

    (Universidad Autónoma Metropolitana-Azcapotzalco. Departamento de Sistemas.)

  • Lara Velázquez, Pedro

    (Universidad Autónoma Metropolitana-Azcapotzalco. Departamento de Sistemas.)

  • de-los-Cobos-Silva, Sergio Gerardo

    (Universidad Autónoma Metropolitana-Iztapalapa. Departamento de Ingeniería Eléctrica.)

Abstract

Compactness is an important principle in redistricting process, and there are different measures to quantify this property in electoral zones. However, these measures are unsatisfactory, since they can be unable to favor the design of compact zones in enough complicated problems. In this paper, we propose that a compactness measure may be unable to promote the design of compact zones without an appropriate algorithm used to explore the solution space. Thus, we design two different heuristic algorithms based on simulated annealing, that use the same compactness measure. They were applied in Baja California, Mexico, which topographical settings cause some traditional compactness measures to give very poor quality results. The differences between the solutions show that the design of compact zones requires not only a compactness measure but also an appropriate algorithm.

Suggested Citation

  • Rincón García, Eric Alfredo & Gutiérrez Andrade, Miguel Ángel & Ramírez Rodríguez, Javier & Lara Velázquez, Pedro & de-los-Cobos-Silva, Sergio Gerardo, 2010. "Applying simulated annealing to design compact zones," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 0(2), pages 11-24, November.
    • Handle: RePEc:fzy:fuzeco:v:xv:y:2010:i:2:p:11-24
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    More about this item

    Keywords

    Redistricting; Compactness; Simulated Annealing; Gerrymandering.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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