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In this paper we introduce a new class of stochastic Petri nets in which one or more places can hold uid rather than discrete tokens. We deene a class of uid stochastic Petri nets in such a way that the discrete and continuous portions may aaect each other. Following this deenition we provide equations for their transient and steady-state behavior. We(More)
A new iterative algorithm, the <italic>multi-level</italic> algorithm, for the numerical solution of steady state Markov chains is presented. The method utilizes a set of recursively coarsened representations of the original system to achieve accelerated convergence. It is motivated by multigrid methods, which are widely used for fast solution of partial(More)
Recently the Multi-Level algorithm was introduced as a general purpose solver for the solution of steady state Markov chains. In this paper we consider the performance of the Multi-Level algorithm for solving Nearly Completely Decomposable (NCD) Markov chains, for which special-purpose iterative aggregation/disaggregation algorithms such as the(More)
This paper is concerned with the simulation analysis of discrete-state stochastic models such as queueing systems or stochastic Petri nets, in which arbitrary probability distributions may be assigned to the activities. The analysis is performed on the state space using a numerical approach, rather than the usual discrete-event simulation at the model(More)
In this paper we i n troduce a new class of stochastic Petri nets in which one or more places can hold uid rather than discrete tokens. We dene a class of uid stochastic Petri nets in such a w a y that the discrete and continuous portions may aect each other. Following this denition we provide equations for their transient and steady-state behavior. We(More)
Zusammenfassung Fourier Mode Analysis of the Muitigrid Waveform Relaxation and Time-Parallel Multigrid Methods. The advent of parallel computers has led to the development of new solution algorithms for time-dependent partial differential equations. Two recently developed methods, multigrid waveform relaxation and time-parallel multigrid, have been designed(More)
This paper combines two diierent extensions of the modeling power of stochastic Petri nets in one single framework. First, the ring times of transitions may be non-exponentially distributed. Second, certain places can hold a continuous ((uid), rather than discrete, number of tokens. Both extensions lead to a state space which is partially discrete and(More)
The analysis of discrete stochastic models such as generally distributed stochastic Petri nets can be done using state space-based methods. The behavior of the model is described by a Markov chain that can be solved mathematically. The phase-type distributions that are used to describe non-Markovian distributions have to be approximated. An approach for the(More)
Previous research has shown that diversity within distributed collaborative teams can lead to innovation, but trust must exist for the open expression of innovative ideas and establishment of idea credibility. Initial trust is pivotal for distributed teams where team members have never met face-to-face and have only a very limited time to accomplish a task.(More)
In this paper, hidden Markov model algorithms are considered as a method for computing conditional properties of continuous-time stochastic simulation models. The goal is to develop an algorithm that adapts known hidden Markov model algorithms for use with proxel-based simulation. It is shown how the forward- and Viterbi-algorithms can be directly(More)