Simulation Methodology
Abstract
Our work on simulation methodology begins with the formulation of a model as a stochastic process. We then use the structure of the stochastic process to develop methods for analyzing the output of the simulation. Diagram 1 is a block diagram which details our approach to system simulation. The performance evaluation and reliability analysis of complex engineering systems requires an ability to analyze mathematical models of these systems. Large scale stochastic models are required to handle various uncertainties present in these systems. Unfortunately, the complexity of most stochastic models of real systems is well beyond our ability to apply classical mathematical analysis. Computer simulation of stochastic systems has become one of the principal alternatives to classical analysis. The main thrust of our research is improving the efficiency of simulation methods and extending their applicability to wider class of stochastic systems. We also carry out research on a variety of stochastic models with the aim of obtaining closed form solutions or approximations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1998
- Accession Number
- ADA358475
Entities
People
- Donald Iglehart
- Peter W. Glynn
Organizations
- Stanford University