Developing a Mathematical Model for Scheduling and Determining Success Probability of Research Projects Considering Complex-Fuzzy Networks

Table 5

Input parameters of activity network without any loops.

Code of activity	Initial fuzzy duration of activity performance	Final fuzzy duration of activity performance	Success probability of activity	Occurrence probability of activity
0-1	(4, 5, 6, 7)	(4, 5, 6, 7)	1	1
1-2	(7, 9, 10, 11)	(16.8, 21.31, 24.38, 27.85)	0.84	1
2-3	(2, 3, 4, 5)	(7.57, 10.01, 12.23, 14.85)	0.82	1
3-4	(8, 9, 10, 11)	(11.53, 13.33, 15.03, 16.89)	0.81	0.6
3-13	(12, 14, 15, 18)	(15.53, 18.33, 20.03, 23.89)	0.76	0.4
4-5	(3.17, 4.71, 5.94, 7.66)	(3.17, 4.71, 5.94, 7.66)	0.99	1
5-13	(1, 2, 2, 3)	(1, 2, 2, 3)	0.9	1
13-15	(1, 1, 2, 2)	(1, 1, 2, 2)	1	1
0-6	(4, 5, 6, 8)	(4, 5, 6, 8)	1	1
6-7	(2, 3, 3, 4)	(2, 3, 3, 4)	1	1
7-8	(4, 5, 6, 7)	(4, 5, 6, 7)	0.95	1
8-9	(3, 4, 4, 5)	(5, 6.67, 6.67, 8.33)	0.84	1
9-10 (d)	(3, 4, 5, 6)	(3, 4, 5, 6)	0.9	0.42
9-10 (e)	(2, 4, 5, 7)	(2, 4, 5, 7)	0.8	0.58
10-14	(1, 1, 1, 1)	(1, 1, 1, 1)	1	1
6-11	(2, 3, 3, 4)	(2, 3, 3, 4)	1	1
11-12	(6, 7, 8, 9)	(8.91, 10.6, 12.29, 13.73)	0.68	1
12-14	(1, 2, 2, 3)	(1.54, 3.08, 3.62, 4.62)	0.9	1
14-15	(2, 3, 4, 4)	(2, 3, 4, 4)	1	1
15-16	(4, 5, 6, 7)	(4, 5, 6, 7)	1	1
16-17	(1, 2, 2, 3)	(1, 2, 2, 3)	1	1