一类确定性随机Petri网暂态分析的有效算法

M. Gribaudo, M. Sereno
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引用次数: 2

摘要

提出了一种求解确定性随机Petri网(DSPN)子类的暂态解的新算法。该技术可以应用于仅包含确定性转换和即时转换的dspn,并且在每个有形标记中仅启用一个确定性转换。该算法不需要对具有任何正实值的确定性转移延迟进行任何额外的限制。文献中提出的大多数优化算法都是基于控制与DSPN相关的随机过程的方程的有效解;我们提出的新算法是基于对DSPN底层状态空间内路径的有效组合分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An efficient algorithm for the transient analysis of a class of deterministic stochastic Petri nets
In this paper a new algorithm for the transient solution of a sub-class of deterministic stochastic Petri nets (DSPN) is proposed. The technique can be applied to DSPNs comprising only deterministic and immediate transitions and such that in each tangible marking only one deterministic transition is enabled. The algorithm does not require any additional restriction on the deterministic transition delays that can have any positive real value. Most of the optimized algorithms presented in the literature are based on an efficient solution of the equations governing the stochastic process associated with the DSPN; the new algorithm we propose is based on an efficient combinatorial analysis of the paths within the state space underlying the DSPN, instead.
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