This paper demonstrates how fuzzy expert systems can be integrated within discrete event simulation models to enhance their modeling and predictive capabilities for construction engineering applications. A proposed methodology is presented for extracting the information from experts to develop the fuzzy expert system rules. The developed fuzzy expert system is integrated within a discrete event simulation model to enhance its modeling capability by explicitly accounting for the different factors affecting some of the simulation activities. A tunneling case study is used to illustrate the features of the integrated system. The outputs generated from the integrated system are very comparable to those from the original probabilistic simulation model. The integrated system represents a more realistic modeling scenario, since it thoroughly accounts for the different factors affecting the tunnel boring machine (TBM) advance rate. This paper is relevant to researchers because it provides an advance in combining artificial intelligence techniques with simulation models to yield better tools for construction modeling. It is of relevance to practitioners because it provides a useful tool for modeling construction engineering problems.
Real-time discrete event simulation: a framework for an intelligent expert system approach utilising decision trees
