Stochastic Petri nets have been used to analyze the performance and re
liability of complex systems comprising concurrency and synchronizatio
n. Various extensions have been proposed in literature in order to bro
aden their field of application to an increasingly larger range of rea
l situations. In this paper we extend the class of Markov regenerative
stochastic Petri nets (MRSPNs*), removing the restriction that at mo
st one generally distributed timed transition can be enabled in ally m
arking. This new class of Petri nets, which we call concurrent general
ized Petri nets (CGPNs), allows simultaneous enabling of immediate, ex
ponentially and generally distributed timed transitions, under the hyp
othesis that the latter are all enabled at the same instant. The stoch
astic process underlying a CGPN is shown to be still an MRGP. We evalu
ate the kernel distribution of the underlying MRGP and define the step
s required to generate it automatically. The methodology described is
used to assess the behavior of a system in both steady-state and trans
ient functioning conditions. (C) 1998 Elsevier Science B.V.