| (1) Initialize the data; |
| (2) For = 1 to do // is the number of iterations |
| (3) Randomly generate a weight vector based on the prior weight information; |
| (4) Randomly generate a set of sub-criteria values (, , , , , ); |
| (5) Calculate ( = 1, 2, 3) for each , using (1); |
| (6) Calculate ( = 1, 2, 3) for each , using (24); |
| (7) Calculate for each using (15); |
| (8) Sort according to the size of ; getting ; // represents the sorting of in iteration . |
| (9) If rank the first, then ; |
| (10) End for |
| (11) For = 1 to do |
| (12) For = 1 to do |
| (13) ; // is the total number of times that obtains rank ; |
| (14) ; |
| (15) End for |
| (16) Calculate according to (21); |
| (17) End for |
| (18) For = 1 to do |
| (19) ; |
| (20) End for |
| (21) For = 1 to do // is the number of iterations |
| (22) Randomly generate a set of sub-criteria values (, , , , , ); |
| (23) Calculate ( = 1, 2, 3) for each , using (1); |
| (24) Calculate ( = 1, 2, 3) for each , using (24); |
| (25) For = 1 to do |
| (26) ; |
| (27) Calculate for each using (15); |
| (28) Sort according to the size of ; |
| (29) If rank the first, then ; |
| (30) End for |
| (31) End for |
| (32) For = 1 to do |
| (33) ; |
| (34) End for |
