Abstract
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.
Original language | English (US) |
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Pages (from-to) | 59-79 |
Number of pages | 21 |
Journal | SIAM Journal on Applied Mathematics |
Volume | 68 |
Issue number | 1 |
DOIs | |
State | Published - 2007 |
Keywords
- Boltzmann equation
- Fluid limits
- Mean field theories
- Supply chains
- Traffic flow models
ASJC Scopus subject areas
- Applied Mathematics