Randomness Modeling in Supply Chain Simulation

Proceedings of the First International Conference on Intelligent Systems, Modelling and Simulation (ISMS 2010) 2010
Gaļina Merkurjeva, Oļesja Večerinska

Stochastic simulation models utilize probability distributions to represent a multitude of randomly occurring events. Theoretical distributions are commonly used to model the randomness of a real process because they help to smooth data irregularities that may exist due to the values missed during the data collection phase. These distributions can be selected either by fitting a distribution to the data collected, or based on the known properties of the process being modelled. The incompatibility between specific characteristics of the theoretical distribution and assumptions of simulation and mathematical calculus present an actual problem in supply chains. The paper is based on the analysis of mentioned contradictions. Different approaches to deal with theoretical probability distributions in supply chains are described in the paper.

Atslēgas vārdi
simulation; input data; randomness modeling; statistical analysis; normal distribution; truncated distribution
DOI
10.1109/ISMS.2010.34
Hipersaite
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5416106

Merkurjeva, G., Večerinska, O. Randomness Modeling in Supply Chain Simulation. No: Proceedings of the First International Conference on Intelligent Systems, Modelling and Simulation (ISMS 2010), Lielbritānija, Liverpool, 27.-29. janvāris, 2010. Piscataway: IEEE Computer Society, 2010, 128.-133.lpp. ISBN 978-1-4244-5984-1. Pieejams: doi:10.1109/ISMS.2010.34

Publikācijas valoda
English (en)