RT - Journal Article
T1 - Expected Duration of Dynamic Markov PERT Networks
JF - IUST
YR - 2007
JO - IUST
VO - 18
IS - 3
UR - http://ijiepr.iust.ac.ir/article-1-24-en.html
SP - 1
EP - 5
K1 - Keywords : Dynamic Programming
K1 - Stochastic Processes
K1 - Longest Path
K1 - Graph Theory
AB - 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.
LA eng
UL http://ijiepr.iust.ac.ir/article-1-24-en.html
M3
ER -