Boolean constraints. Such criteria are typically
called factors, and express varying degrees of
suitability for the decision under consideration.
Thus, for example, proximity to roads would be
treated not as an all-or-none buffer zone of suitable
locations, but rather, as a continuous expression of
suitability according to a special numeric scale
(e.g. 0–1, 0–100, 0–255, etc.). The process of
converting data to such numeric scales is most
commonly called standardisation (Voogd 1983).
Traditionally, standardised factors are combined
by means of weighted linear combination – that is,
each factor is multiplied by a weight, with results
being summed to arrive at a multi-criteria solution. In
addition, the result may be multiplied (i.e. intersected)
by the product of any Boolean constraints that may
apply (Eastman et al 1995). For example:
suitability = Σ wiXi * Π Cj
where wi = weight assigned to factor i
Xi = criterion score of factor i
Cj = constraint j
Figure 2 illustrates this approach where a
comparable example is developed to that in Figure 1.
Again, the intention is to find areas suitable for
industrial development, subject to the following
Boolean constraints. Such criteria are typicallycalled factors, and express varying degrees ofsuitability for the decision under consideration.Thus, for example, proximity to roads would betreated not as an all-or-none buffer zone of suitablelocations, but rather, as a continuous expression ofsuitability according to a special numeric scale(e.g. 0–1, 0–100, 0–255, etc.). The process ofconverting data to such numeric scales is mostcommonly called standardisation (Voogd 1983).Traditionally, standardised factors are combinedby means of weighted linear combination – that is,each factor is multiplied by a weight, with resultsbeing summed to arrive at a multi-criteria solution. Inaddition, the result may be multiplied (i.e. intersected)by the product of any Boolean constraints that mayapply (Eastman et al 1995). For example:suitability = Σ wiXi * Π Cjwhere wi = weight assigned to factor iXi = criterion score of factor iCj = constraint jFigure 2 illustrates this approach where acomparable example is developed to that in Figure 1.Again, the intention is to find areas suitable forindustrial development, subject to the following
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