Title :
A GSMP formalism for discrete event systems
Author_Institution :
Dept. of Oper. Res., Stanford Univ., CA, USA
fDate :
1/1/1989 12:00:00 AM
Abstract :
A precise mathematical framework for the study of discrete event systems is described. The idea is to define a particular type of stochastic process, called a generalized semi-Markov process (GSMP), which captures the essential dynamical structure of a discrete event system. An attempt is also made to give the flavor of the qualitative theory and numerical algorithms that can be obtained as a result of viewing discrete event systems as GSMPs. Likelihood ratio concepts for importance sampling are briefly described
Keywords :
Markov processes; discrete time systems; dynamics; probability; stochastic processes; discrete event systems; dynamical structure; dynamics; generalised semiMarkov process; likelihood ratio; sampling; stochastic process; Discrete event simulation; Discrete event systems; Monte Carlo methods; Operations research; Stochastic processes;
Journal_Title :
Proceedings of the IEEE
