Semivariogram-based distance function for gradual coverage location models

Location models that employ gradual coverage require the integration of a distance function, either within the objective function or among the constraints. Existing studies in this area often utilize linear or exponential distance functions as examples. However, the choice of distance function can s...

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Bibliographic Details
Published in:Expert systems with applications 2025-04, Vol.267, Article 126167
Main Authors: Simoyama, Felipe O., Curtin, Kevin M., Croope, Silvana, de Salles Neto, Luiz Leduino, Santos, Leonardo Bacelar Lima
Format: Article
Language:English
Subjects:
Gradual coverage
Location models
Semivariogram
Online Access:Get full text
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Summary:Location models that employ gradual coverage require the integration of a distance function, either within the objective function or among the constraints. Existing studies in this area often utilize linear or exponential distance functions as examples. However, the choice of distance function can significantly impact the outcomes. For scenarios with higher uncertainty, employing a tailor-made function that incorporates data specific to the study area can be advantageous. This research introduces the use of distance functions derived from variograms in gradual coverage location models. We present two case studies focusing on the design of flood monitoring networks, comparing the effectiveness of various variogram models in these contexts.
ISSN:0957-4174
DOI:10.1016/j.eswa.2024.126167