Implementing various stochastic optimization algorithms for Markov decision processes for use in manufacturing and retail establishments
This project is more theoretical in nature. We are trying to adapt our structural dependence probability models into a more general measure-theoretic framework.
We propose a new type of time series modeling called fuzzy ARIMA, in which we aggregate high granularity data sets into fuzzy numbers, thus avoiding the typical loss of information when aggregation is performed.