It is well understood that randomness in manufacturing systems is a common occurrence due to machine breakdowns, maintenance and many other factors. Recent studies show that jump diffusions are good approximations for these analytically intractable systems. The objective of this research is to model and analyze the stochastic resource allocation problem in multiple class jump diffusion networks which arise in production systems and computer communication networks. A stochastic intensity model allows resource allocation problems to be described in terms of intensity scheduling and drift control. With such a framework, schedulings in discrete queueing network model and fluid network model turn out to be special cases. This research will characterize, compute, and search for heuristics of the optimal allocation rule by defining allocation rules using state space decomposition and finding sufficient optomality condition on the defined control sets. Intuitive scheduling control rules will be obtained by simulation; and the conjectured results will be verified using discrete time approximation.
