Authors:
Bajis M. Dodin
1
and
Abdelghani A. Elimam
2
Affiliations:
1
Alfaisal University, Saudi Arabia
;
2
American University in Cairo, Egypt
Keyword(s):
Probabilistic Durations, Network Structure, Simulation, Sample Size, Project Variance.
Related
Ontology
Subjects/Areas/Topics:
Application Domains
;
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Case Studies
;
Computing and Telecommunications in Cardiology
;
Construction Engineering and Project Management
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Domain-Specific Tools
;
Formal Methods
;
Health Engineering and Technology Applications
;
Knowledge-Based Systems
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Simulation and Modeling
;
Simulation Tools and Platforms
;
Stochastic Modeling and Simulation
;
Symbolic Systems
Abstract:
Stochastic Activity Networks (SANs) are used in modeling and managing projects that are characterized by
uncertainty. SANs are primarily managed using Monte Carlo Sampling (MCS). The accuracy of the results
obtained from MCS depends on the sample size. So far the required sample size has been determined
arbitrarily and independent of the characteristics of the SAN such as the number of activities and their
underlying distributions, number of paths, and the structure of the SAN. In this paper we show that the
accuracy of the SANs simulation results would depend on the sample size. Contrary to existing practices,
we show that such sample size must reflect the project size and structure, as well as the number of activities.
We propose an optimization-based approach to determine the project variance, which in turn is used to
determine the number of replications in SAN simulations.