Stochastic Dynamics of Long Supply Chains with Random Breakdowns

We analyze the stochastic large time behavior of long supply chains via a traffic flow random particle model. As items travel on a virtual road from one production stage to the next, random breakdowns of the processors at each stage are modeled via a Markov process. The result is a conservation law...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:SIAM Journal on Applied Mathematics. - Society for Industrial and Applied Mathematics, 1966. - 68(2007), 1, Seite 59-79
1. Verfasser: Degond, P. (VerfasserIn)
Weitere Verfasser: Ringhofer, C.
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2007
Zugriff auf das übergeordnete Werk:SIAM Journal on Applied Mathematics
Schlagworte:supply chains traffic flow models mean field theories Boltzmann equation fluid limits Economics Applied sciences Physical sciences Philosophy Mathematics
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520 |a We analyze the stochastic large time behavior of long supply chains via a traffic flow random particle model. As items travel on a virtual road from one production stage to the next, random breakdowns of the processors at each stage are modeled via a Markov process. The result is a conservation law for the expectation of the part density which holds on time scales which are large compared to the mean up and down times of the processors. 
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650 4 |a Physical sciences  |x Physics  |x Mechanics  |x Density 
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