Research Dr. Durai Sundaramoorthi's current research focuses on Simulation Modeling and Optimization of Stochastic Systems (SIMMOSS). Most of the systems in the real world are too complex and uncertain to use traditional math modeling approaches for analysis. In such situations, simulation modeling is a good choice for analyzing, evaluating and optimizing the system. Availability of RFID and other latest technologies have enabled data collection from complex systems and utilization of dataintegrated techniques for simulation. His primary expertise is in using treebased data mining techniques to simulate Markoviantype stochastic in the system. In traditional stochastic simulation models, transition probabilities are obtained either subjectively or by looking at all of the possible combinations of the levels of the simulation state variables. If the system under consideration is complex, then a subjective approach is unlikely to be accurate, and an approach using all of the possible combinations of the states will be impractical. For instance, six categorical variables with ten categories each will lead to a million possible states in the simulation. Obtaining accurate transition probabilities for such a huge simulation model is difficult. In his research, using data from
