| Input: Ids, locations, weights |
| Output: collection point clusters |
| (1) | % initalize each point as a clusters |
| (2) | clus←Ids |
| (3) | cluWts←weights |
| (4) | CPs←locations |
| (5) | % obtain the distance matrix C |
| (6) | C← distance (CPs[i], CPs[J]) |
| (7) | % obtain pairs P that will be merged (getP) |
| (8) | X, Y←obtain the two closest clusters according to C |
| (9) | % obtain the cluster Z after X and Y are merged |
| (10) | Z←merge (clus [X], clus [Y]) |
| (11) | % obtain the operating cost of the cluster Z |
| (12) | costZ←get cost (Z) |
| (13) | % obtain the operating cost of the clus [X] and the clus [Y] |
| (14) | costX←get cost (clus [X]) |
| (15) | costY←get cost (clus [Y]) |
| (16) | if (clusWts [X] + clusWts [Y]) ≤ M and costZ ≤ (costX + costY) then |
| (17) | P append ((X, Y)) |
| (18) | end if |
| (19) | % If P is not empty, loop to merge clusters |
| (20) | While P←getP () is not null do |
| (21) | % Merge the clusters (X, Y) in P, and update related variables |
| (22) | clus [X]←Z |
| (23) | remove clus [Y] |
| (24) | CPs [X]←get Center (clus [X]) |
| (25) | removeCPs [Y] |
| (26) | clusWts [X]←(clusWts [X] + clusWts[Y]) |
| (27) | remove clusWts [Y] |
| (28) | update C |
| (29) | P clear () |
| (30) | end While |
| (31) | return clus |
