Abstract
The family of outranking methods includes a set of well‐known and popular decision‐aid methods. Heterogeneous variables of various scales can be introduced, and data transformations are not required. But it is also recognized that these methods are subject to computational limitations with respect to the number of decision alternatives. Dealing with large raster datasets and considering every raster cell a location alternative, these methods reach their computational limits quickly. This paper discusses these computational limits and presents an iterative approach which enables a modeller to easily and transparently apply outranking methods for land‐suitability assessment with practically no limit in the sizes of the raster datasets. An example using the PROMETHEE outranking approach is performed.
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