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

Table 4

Input parameters of activity network.

Code of activity	Duration (week)	Success probability of activity/loop	Occurrence probability of activity/loop
0-1	(4, 5, 6, 7)	1	1
1-2	(7, 9, 10, 11)	0.9	1
2-3	(2, 3, 4, 5)	0.9	1
3-4	(8, 9, 10, 11)	0.85	0.6
3-13	(12, 14, 15, 18)	0.8	0.4
4-5 (a)	(2, 3, 4, 5)	0.8	0.7
4-5 (b)	(2, 4, 5, 7)	0.8	0.2
4-5 (c)	(6, 7, 8, 10)	0.85	0.1
5-3	(0, 0, 0, 0)	1	0.4
5-2	(0, 0, 0, 0)	1	0.25
5-13	(1, 2, 2, 3)	0.9	0.35
13-15	(1, 1, 2, 2)	1	1
0-6	(4, 5, 6, 8)	1	1
6-7	(2, 3, 3, 4)	1	1
7-8	(4, 5, 6, 7)	0.95	1
8-9	(3, 4, 4, 5)	0.9	1
9-8	(0, 0, 0, 0)	1	0.4
9-10 (d)	(3, 4, 5, 6)	0.9	0.25
9-10 (e)	(2, 4, 5, 7)	0.8	0.35
10-14	(1, 1, 1, 1)	1	1
6-11	(2, 3, 3, 4)	1	1
11-12	(6, 7, 8, 9)	0.8	1
12-11	(0, 0, 0, 0)	1	0.3
12-12	(1, 2, 3, 3)	1	0.35
12-14	(1, 2, 2, 3)	0.9	0.35
14-15	(2, 3, 4, 4)	1	1
15-16	(4, 5, 6, 7)	1	1
16-1	(0, 0, 0, 0)	1	0.2
16-17	(1, 2, 2, 3)	1	0.8