The goal of this research project is to develop a new approach for the modelling, analysis and design of stochastic discrete event dynamic systems (DEDS). The proposed approach is based on obtaining the Maclaurin series of the performance measure as a function of a decision parameter. Our objectives are (i) to develop efficient recursive expressions for the Maclaurin coefficients for a large class of stochastic DEDS and (ii) to investigate the theoretical and practical implications of the obtained Maclaurin series. The results of this project would form a powerful complement to existing methodologies for stochastic DEDS. In particular, we will develop simple closed form approximations of the performance measures for the purpose of analysis and design, as well as some stochastic DEDS modelling guidelines analogous to those in the classical Bode-Nyquist methodology for modelling continous variable dynamic systems.
