1. An apparatus comprising: an analytic network process (ANP) storage memory that stores an ANP weighted supermatrix representing an ANP model; and a processor in communication with the ANP storage memory, the processor being configured to facilitate changing priorities of a node in the ANP weighted supermatrix to be more important, and changing priorities of the node in the ANP weighted supermatrix to be less important; assessing a sensitivity of the node itself which was changed relative to the ANP model; and maintaining a same proportionality in the ANP weighted supermatrix for the changing of the priorities and the assessing of the relative sensitivity, wherein the sensitivity of the node itself is assessed by changing, by a same predetermined amount, each entry throughout a same row of the node of the ANP weighted supermatrix and consequently rescaling the rest of the entries in a column of the ANP weighted supermatrix that corresponds to the node being assessed, the changing comprising, for all 0≦p≦1, defining F W,r,p 0 (p) by changing the r th row and then rescaling the remaining entries in the columns so that the columns continue to add to one; rescaling to be less important comprising, for 0≦p≦p 0 , changing the r th row by scaling it by p p 0 ; rescaling to be more important comprising, for p 0 ≦p≦1, changing the entries in the r th row consistent with the following formula 
 F W,r,p 0 ( p ) r,j =1−α(1 −W r,j ) where α = 1 - p 1 - p 0 ; where the ANP model M is fixed, W is a weighted supermatrix of the ANP model M whose dimensions are n×n, r is a row and is an integer fixed between 1 and n, j is a column, p is a parameter value and p 0 is an initial value of p, 0<p 0 <1, F W,r,p 0 :[0, 1]→M n,n ([0, 1]) is a family F of perturbations of W in the r th row, and trivial columns are left unchanged throughout the family of row perturbations of the ANP model.