| Require: seq ≔ vector of expected number of neighbors |
| Require: liste
≔ vector of criterion values |
| (1) for all seq do |
| (2) Compute the binary matrix of common neighbors for seq |
| (3) Compute the scalar products matrix of |
| (4) () (sort the individuals) |
| (5) (, ), compute the criterion |
| (6) liste(liste, ) |
| (7) end for |
| (8) arg |
| (9) |
| (10) |
| The PB-Clus algorithm returns the minimum of the criterion , |
| the related number of common neighbors and the optimal sorting matrix . |
| (1) procedure SORT() |
| (2) (, ) |
| (3) liste ≔ list of individuals whose common neighbors () is non-zero () |
| (4)
≔ the individual for which is maximum |
| (5)
≔ 0 (list containing the ranking value of the individuals) |
| (6) repeat |
| (7) merge(.perm, liste[.col]) |
| (8) if length(.cor) ≥ 1 then |
| (9) [(.cor, .ind), (.cor, .ind)] |
| (10) [(.cor, .ind)] |
| (11) if length(.cor) > 1 then |
| (12) (1, ) |
| (13) end if |
| (14) else |
| (15) [.ind, .ind] |
| (16) liste = liste[.ind] |
| (17) if length(.cor) > 1 then |
| (18) = arg () |
| (19) [.ind, .ind] |
| (20) colinear(, ) |
| (21) end if |
| (22) end if |
| (23) until length(liste) > 1 |
| (1) procedure COLINEAR(, ) returns 3 different lists |
| (2)
≔
th line of |
| (3) .col ≔ list of individuals that are colinear with |
| (4) .cor ≔ list of individuals that are correlated with |
| (5) .ind ≔ list of individuals that are independent of |
