TY - JOUR
T1 - Expected Duration of Dynamic Markov PERT Networks
TT -
JF - IUST
JO - IUST
VL - 18
IS - 3
UR - http://ijiepr.iust.ac.ir/article-1-24-en.html
Y1 - 2007
SP - 1
EP - 5
KW - Keywords : Dynamic Programming
KW - Stochastic Processes
KW - Longest Path
KW - Graph Theory
N2 - Abstract : In this paper , we apply the stochastic dynamic programming to approximate the mean project completion time in dynamic Markov PERT networks. It is assumed that the activity durations are independent random variables with exponential distributions, but some social and economical problems influence the mean of activity durations. It is also assumed that the social problems evolve in accordance with the independent semi-Markov processes over the planning horizon. By using the stochastic dynamic programming, we find a dynamic path with maximum expected length from the source node to the sink node of the stochastic dynamic network. The expected value of such path can be considered as an approximation for the mean project completion time in the original dynamic PERT network.
M3
ER -