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Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms

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García-Alonso, Carlos R., Pérez-Naranjo, Leonor M., Fernández-Caballero, Juan C.·2014·Annals of Operations Research
DOI 10.1007/s10479-011-0841-3
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Abstract

Local Indicators of Spatial Aggregation (LISA) can be used as objectives in a multicriteria framework when highly autocorrelated areas (hot-spots) must be identified and geographically located in complex areas. To do so, a Multi-Objective Evolutionary Algorithm (MOEA) based on SPEA2 (Strength Pareto Evolutionary Algorithm v.2) has been designed to evaluate three different fitness functions (fine-grained strength, the weighted sum of objectives and fuzzy evaluation of weighted objectives) and three LISA methods. MOEA makes it possible to achieve a compromise between spatial econometric methods as it highlights areas where a specific phenomenon shows significantly high autocorrelation. The spatial distribution of financially compromised olive-tree farms in Andalusia (Spain) was selected for analysis and two fuzzy hot-spots were statistically identified and spatially located. Hot-spots can be considered to be spatial fuzzy sets where the spatial units have a membership degree that can also be calculated.

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Metadata

Authors
García-Alonso, C. R., Pérez-Naranjo, L. M., & Fernández-Caballero, J. C.
Venue
Annals of Operations Research
Publisher
Springer Science and Business Media LLC
Published
2011-01-20
Volume
219
Issue
1
Pages
187-202
ISSN
  • 0254-5330 (ISSN-L)
  • 1572-9338
DOI
10.1007/s10479-011-0841-3
OpenAlex
W2060300932
Cited by
1,353
References
2
FWCI
1.20
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

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García-Alonso, C. R., Pérez-Naranjo, L. M., & Fernández-Caballero, J. C. (2014). Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms. Annals of Operations Research. https://doi.org/10.1007/s10479-011-0841-3

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