Simulation of large networks: propagation of uncertainty in a simulation-based maritime risk assessment model utilizing Bayesian simulation techniques

Authors:
Jason R. W. Merrick;Varun Dinesh;Amita Singh;J. René van Dorp;Thomas A. Mazzuchi
Affiliations:
Virginia Commonwealth University, Richmond, VA;Virginia Commonwealth University, Richmond, VA;George Washington University, Washington, D.C.;George Washington University, Washington, D.C.;George Washington University, Washington, D.C.
Venue:
Proceedings of the 35th conference on Winter simulation: driving innovation
Year:
2003

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Abstract

Recent studies in the assessment of risk in maritime transportation systems have used simulation-based probabilistic techniques. Amongst them are the San Francisco Bay (SFB) Ferry exposure assessment in 2002, the Washington State Ferry (WFS) Risk Assessment in 1998 and the Prince William Sound (PWS) Risk Assessment in 1996. Representing uncertainty in such simulation models is fundamental to quantifying system risk. This paper illustrates the representation of uncertainty in simulation using Bayesian techniques to model input and output uncertainty. These uncertainty representations describe system randomness as well as lack of knowledge about the system. The study of the impact of proposed ferry service expansions in San Francisco Bay is used as a case study to demonstrate the Bayesian simulation technique. Such characterization of uncertainty in simulation-based analysis provides the user with a greater level of information enabling improved decision making.