Compacidad en celdas aplicada al diseño de zonas electorales
DOI:
https://doi.org/10.18381/eq.v5i2.95Resumen
El diseño de zonas electorales es un problema que busca garantizar la democracia mediante la aplicación de condiciones tales como: equilibrio poblacional, conexidad y compacidad geométrica. En este artículo se propone el uso de una nueva medida de compacidad geométrica, que mide la calidad de las zonas electorales construidas mediante una malla formada con celdas cuadradas. Para determinar su eficiencia se diseñó una metodología que permite obtener mallas tan pequeñas como el estudio lo requiera. Finalmente se eligió un caso de estudio, cuya configuración topográfica provoca que algunas medidas de compacidad tradicionales den resultados de calidad muy pobre y, debido a la complejidad computacional del problema, se diseñó un algoritmo basado en recocido simulado. Los resultados obtenidos muestran que la nueva medida favorece la creación de zonas con formas rectas y evita las figuras retorcidas o dispersas, dando como resultado zonas de muy buena calidad.Descargas
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Altman, M. (1997). “Is Automation the Answer: The Computational Complexity of Automated Redistricting”, Rutgers Computer and Law Technology Journal, 23(1), pp. 81-141.
Altman, M. (1998). “Traditional Districting Principles: Judicial Myths vs. Reality”. Social
Science History, 22(2), pp. 159-200.
Baçao, F., Lobo, V., Painho, M. (2005). “Applying genetic algorithms to zone design”.
Soft Comput, 9, pp. 341-348.
Bergey, P. K., Ragsdale, C. T., Hoskote, M. (2003). “A Simulated Annealing Genetic Algorithm for the Electrical Power Districting Problem”. Annals of Operations Research, 121, pp. 33–55.
Blair, D. J., Biss, T. H. (1967). “The Measurement of Shape in Geography: An Appraisal of Methods and Techniques”. Bulletin of Quantitative Data for Geographers, 11, Nottingham University.
Blais, M., Lapierre, S. D., Laporte, G. (2003). “Solving a home-care districting problem in an urban setting”. Journal of the Operational Research Society, 54, pp. 1141-1147.
Bong, C. W., Wang, Y. C. (2006). “A Multiobjective Metaheuristic for Spatial-based Redistricting”. Int. J. Services Operations and Informatics, 1(1y2), pp. 146-164.
Bozkaya, B., Erkut, E., Laporte, G. (2003). “A tabu search heuristic and adaptive memory procedure for political districting”. European Journal of Operational Research, 144, pp. 12–26.
Bribiesca, L. (1997). “Measuring 2-D shape compactness using the contact perimeter”.
Computers Math. Applic. 33(11), pp. 1–9.
Caro, F., Shirabe, T., Guignard, M., Weintraub, A. (2004). “School redistricting: embedding GIS tools with integer programming”. Journal of the Operational Research
Society, 55, pp. 836–849.
Cerny, V. (1985). “A thermodynamical approach to the travelling salesman problem: an efficient simulation algorithm”. Journal of Optimization Theory and Applications, 45, pp. 41-55.
Chou, C., Li, S. P. (2006). “Taming the Gerrymander-Statistical physics approach to Political Districting Problem”. Physica A, 369, pp. 799–808.
Chou, C., Li, S. P. (2007). “Spin systems and Political Districting Problem”. Journal of
Magnetism and Magnetic Materials, 310, pp. 2889–2891.
Cirincione, C., Darling, T. A., O’Rourke, T. G. (2000). “Assessing South Carolina’s 1990s congressional districting”. Political Geography, 19, pp. 189–211.
Cova, J. T., Church, R. L. (2000). “Contiguity Constraints for Single Region Site Search Problems”. Geographical Analysis, 32(4), pp. 306–29.
D’Amico, S., Wang, S., Batta, R., Rump, C. (2002). “A simulated annealing approach to police district design”. Computers & Operations Research, 29, pp. 667–684. desJardins, M., Bulka, B., Carr, R., Jordan, E., Rheingans, P. (2006). “Heuristic search and information visualization methods for school redistricting”. AI Magazine, 28(3), pp 59–72.
Ferland, J., Guenette, G. (1990). “Decision Support System for the School Districting Problem”. Operations Research, 38(1), pp. 15– 21.
Gilbert, K. C., Holmes, D. D., Rosenthal, R. E. (1985). “A Multiobjective Discrete Optimization Model for Land Allocation”. Management Science, 31(12), pp. 1509-1522.
Glover, F., Ghaziri, H. M., González, J. L., Laguna, M., Moscato, P., Tseng, F. T. (1996).
Optimización heurística y redes neuronales. Ed. Paraninfo, Madrid, España .
Hayes, B. (1996). “Machine politics”. American Scientist. Research triangle park, 84(6), pp. 522-526.
Hess, S. W., Weaver, J. B., Siegfeldt, H. J., Whelan, J. N., Zitlau, P. A. (1965). “Nonpartisan Political Redistricting by Computer”. Operations Research, 13(6), pp. 998-1006.
He, S., Samuels, S. (1971). “Experiences with a Sales Districting Model: Criteria and Implementation”. Management Science, 18(4), Application Series, Part 2, Marketing Management Models, pp. 41-54.
I.F.E. (2004). Gaceta electoral. I.F.E., 18, pp. 119-134.
Kirkpatrick, S., Gellat, C. D. Vecchi, M. P. (1983). “Optimization by simulated annealing”. Science, 220, pp. 671-680.
Macmillan, W. (2001). “Redistricting in a GIS environment: An optimisation algorithm using switching-points”. Journal of geographical systems, 3, pp. 167-180.
Mehrotra, A., Johnson, E. L., Nemhauser, G. L. (1998). “An Optimization Based Heuristic for Political Districting”. Management Science, 44(8), pp. 1100-1114.
Metropolis, N., Rosenbluth, A.W., Rosenbluth, M. N., Teller, A. H., Teller, E. (1953). “Equation of state calculation by fast computing machines”. Journal of Chemistry Physics, 21, pp. 1087- 1091.
Muyldermans, L., Cattrysse, D., Van Oudheusden, D., Lotan T. (2002). “Districting for salt spreading operations”. European Journal of Operational Research, 139, pp. 521–532.
Niemi, R. G., Grofman, B., Carlucci, C., Hofeller, T. (1990). “Measuring Compactness and the Role of a Compactness Standard in a Test for Partisian and Racial Gerrymandering”,
Journal of Politics, 52(4), pp. 1155-1181. Ríos-Mercado, R. Z., Fernández, E. (2009). “A reactive GRASP for comercial territory design problem with multiple balancing requirements”. Computers & Operations Research, 36(3), pp 755–776.
Schoepfle, B., Church, R. (1991). “New network representation of a classic school districting problem”. Socio-Econ Plann Sci. 25(3), pp. 189-197.
Segal, M., Weinberger, D. (1977). “Turfing”. Operations Research, 25(3), 367-386.
Shirabe, T. (2005). “A Model of Contiguity for Spatial Unit Allocation”. Geographical
Analysis, 37, pp. 2-16.
Shortt, N. K., Moore, A., Coombes, M., Wymer, C. (2005). “Defining regions for locality health care planning: A multidimensional approach”. Social Science & Medicine, 60, pp. 2715–2727.
Tavares-Pereira, F., Rui, J., Mousseau, V., Roy, B. (2007). “Multiple criteria districting problems: The public transportation network pricing system of the Paris region”. Ann
Oper Res. 154, pp. 69–92.
Vickrey, W. (1961). “On The Prevention of Gerrymandering”. Political Science Quarterly, 76(1), 105-110.
Weaver, J. B., Hess, S. W. (1963). “A Procedure for Nonpartisan Districting: Development of Computer Techniques”. The Yale Law Journal, 73(2), pp. 288-308.
Williams, J. C. (2002). “A Zero-One Programming Model for Contiguous Land Acquisition”. Geographical Analysis, 34(4), pp. 330–49.
Young, H. P. (1988). “Measuring the Compactness Of Legislative Districts”. Legislative
Studies Quarterly. 13(1), pp. 105-115.
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