Research Article

# 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