Algorithms for the generation of state-level representations of stochastic activity networks with general reward structures

M. A. Qureshi; W. H. Sanders; A. P.A. van Moorsel; R. German

Algorithms for the generation of state-level representations of stochastic activity networks with general reward structures

M. A. Qureshi, W. H. Sanders, A. P.A. van Moorsel, R. German

Electrical and Computer Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

Stochastic Petri nets (SPNs) and extensions are a popular method for evaluating a wide variety of systems. In most cases, their numerical solution requires generating a state-level stochastic process, which captures the behavior of the SPN with respect to a set of specified performance measures. These measures are commonly defined at the net level by means of a reward variable. In this paper, discussed are issues regarding the generation of state-level reward models for systems specified as stochastic activity networks (SANs) with 'step-based reward structures.' While discussing issues related to the generation of the underlying state-level reward model, an algorithm to determine whether a given SAN is 'well-specified' is provided.

Original language	English (US)
Pages	180-190
Number of pages	11
State	Published - 1995
Event	Proceedings of the 6th International Workshop on Petri Nets and Performance Models - Durham, NC, USA Duration: Oct 3 1995 → Oct 6 1995

Other

Other	Proceedings of the 6th International Workshop on Petri Nets and Performance Models
City	Durham, NC, USA
Period	10/3/95 → 10/6/95

ASJC Scopus subject areas

Applied Mathematics
Modeling and Simulation

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Algorithms for the generation of state-level representations of stochastic activity networks with general reward structures. / Qureshi, M. A.; Sanders, W. H.; van Moorsel, A. P.A. et al.
1995. 180-190 Paper presented at Proceedings of the 6th International Workshop on Petri Nets and Performance Models, Durham, NC, USA.

Research output: Contribution to conference › Paper › peer-review

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year = "1995",

language = "English (US)",

pages = "180--190",

note = "Proceedings of the 6th International Workshop on Petri Nets and Performance Models ; Conference date: 03-10-1995 Through 06-10-1995",

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AU - Sanders, W. H.

AU - van Moorsel, A. P.A.

AU - German, R.

PY - 1995

Y1 - 1995

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AB - Stochastic Petri nets (SPNs) and extensions are a popular method for evaluating a wide variety of systems. In most cases, their numerical solution requires generating a state-level stochastic process, which captures the behavior of the SPN with respect to a set of specified performance measures. These measures are commonly defined at the net level by means of a reward variable. In this paper, discussed are issues regarding the generation of state-level reward models for systems specified as stochastic activity networks (SANs) with 'step-based reward structures.' While discussing issues related to the generation of the underlying state-level reward model, an algorithm to determine whether a given SAN is 'well-specified' is provided.

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M3 - Paper

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T2 - Proceedings of the 6th International Workshop on Petri Nets and Performance Models

Y2 - 3 October 1995 through 6 October 1995

ER -

Algorithms for the generation of state-level representations of stochastic activity networks with general reward structures

Abstract

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