Stochastic and Kinetic Models in Supply Chain Simulation
Abstract
Stochastic models for individual nodes in a supply chain are based
on randomly selecting throughput times from a time dependent
distribution which depends in general on the state of the node. We
discuss the connection between these models and kinetic - or so
called traffic flow - models and fluid dynamic approximations to
these systems. In the long time average the random model can be
replaced by a deterministic diffusion equation for the expectation
and variance of the output. we discuss the asymptotic procedure, the
numerical solution and present some test results.
(this is joint work with D. Armbruster)
