Approximating the distribution functions in stochastic networks

In this paper an analytical procedure to approximate the distribution functions in stochastic networks is presented. The procedure is efficient in the sense of its accuracy and its computational requirements. Contrary to the existing approximating procedures, it can be applied to large networks. Exa...

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Veröffentlicht in:	Computers & operations research 1985, Vol.12 (3), p.251-264
1. Verfasser:	Dodin, Bajis
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Distribution Exact sciences and technology Functions Mathematical analysis Networks Operational research and scientific management Operational research. Management science Operations research PERT Planning. Forecasting Stochastic models
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	In this paper an analytical procedure to approximate the distribution functions in stochastic networks is presented. The procedure is efficient in the sense of its accuracy and its computational requirements. Contrary to the existing approximating procedures, it can be applied to large networks. Examples and computational experiences involving large networks are provided.
ISSN:	0305-0548 1873-765X 0305-0548
DOI:	10.1016/0305-0548(85)90024-3