一种计算确定性和随机Petri网模型稳态解的改进数值算法

C. Lindemann
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引用次数: 95

摘要

介绍了一种计算DSPN模型稳态解的算法。所描述的方法采用稳定的泊松概率计算增强的随机化技术。在软件包GreatSPN的1.4版本中完全重新设计和重新实现了适当的组件,从而大大节省了计算时间和内存空间。从文献中提取的DSPN模型说明了这些好处。本文研究了E/sub / r//D/1/K排队系统和容错时钟系统的DSPN模型。这些实例表明,与GreatSPN.>软件包1.4版中实现的方法相比,所描述的算法计算模型解的计算量大大减少,并且具有更好的误差控制
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An improved numerical algorithm for calculating steady-state solutions of deterministic and stochastic Petri net models
Introduces an algorithm for calculating steady-state solutions of DSPN models. The described method employs the randomization technique enhanced by a stable calculation of Poisson probabilities. A complete re-design and re-implementation of the appropriate components implemented in the version 1.4 of the software package GreatSPN has lead to significant savings in both computation time and memory space. These benefits are illustrated by DSPN models taken from the literature. The author considers DSPN models for an E/sub r//D/1/K queueing system and a fault-tolerant clocking system. These examples show that the model solutions are calculated with significantly less computational effort and a better error control by the algorithm described than by the method implemented in the version 1.4 of the software package GreatSPN.<>
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