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Spatial Aggregation and Compactness of Census Areas with a Multiobjective Genetic Algorithm: A Case Study in Canada

Author

Listed:
  • Dilip Datta

    (Department of Mechanical Engineering, Tezpur University, Napaam, Tezpur 784028, India)

  • Jacek Malczewski

    (Department of Geography, Social Science Centre, University of Western Ontario, 1151 Richmond Street, London, Ontario, N6A 5C2, Canada)

  • José Rui Figueira

    (CEG-IST, Instituto Superior Técnico, Av. Rovisco Pais, 1049-001 Lisbon, Portugal (also Associate Researcher at LORIA Laboratory, Nancy, France))

Abstract

The paper focuses on a case study of delineating census tracts (CTs) in the Census Metropolitan area of London, Ontario, Canada. The procedure for defining the actual pattern of CTs by a local committee and Statistics Canada has involved such consideration as the compactness of CTs and their population-based and area-based uniformity as well as some subjective aspects. The actual pattern shows that compactness of CTs has been achieved at the expense of uniformity in population and areal sizes. The paper proposes an integer-coded multiobjective genetic algorithm for aggregating census units with the expectation of obtaining a higher level of compactness and population/area uniformity of CTs through an optimization technique. Square-shape and circular-shape compactness of CTs are examined under different scenarios. The results indicate that the proposed genetic algorithm can provide solutions that are considerably better in terms of the Pareto-optimality principle than the actual pattern of CTs.

Suggested Citation

  • Dilip Datta & Jacek Malczewski & José Rui Figueira, 2012. "Spatial Aggregation and Compactness of Census Areas with a Multiobjective Genetic Algorithm: A Case Study in Canada," Environment and Planning B, , vol. 39(2), pages 376-392, April.
    • Handle: RePEc:sae:envirb:v:39:y:2012:i:2:p:376-392
    DOI: 10.1068/b38078
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    References listed on IDEAS

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    1. Bozkaya, Burcin & Erkut, Erhan & Laporte, Gilbert, 2003. "A tabu search heuristic and adaptive memory procedure for political districting," European Journal of Operational Research, Elsevier, vol. 144(1), pages 12-26, January.
    2. 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.
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