Effect of Ignoring Input Correlation on Truck-Shovel Simulation
This paper presents an approach for handling correlated input variables in discrete event simulation (DES) modelling of truck—shovel systems using commercial DES software and uses a case study to investigate the effect of ignoring correlation between input variables. Multivariate random vectors, instead of independent probability distributions, are used for variables found to be correlated. The authors prove that correlations do exist in truck—shovel haulage systems. The model with multivariate random vectors performs better than the original model. The significance of modelling correlation in input variables depends on the strength of the correlation and the output's sensitivity to the input variables.
S. Que et al., "Effect of Ignoring Input Correlation on Truck-Shovel Simulation," International Journal of Mining, Reclamation and Environment, vol. 30, no. 5, pp. 405 - 421, Taylor & Francis, Sep 2016.
The definitive version is available at https://doi.org/10.1080/17480930.2015.1099188
Keywords and Phrases
Commercial vehicles; Computer software; Correlation methods; Probability distributions; Shovels; Trucks; Haulage system; Input correlation; Input variables; Original model; Random vectors; Discrete event simulation; Correlation; Multivariate analysis; Numerical model; Software; Vector; Correlation; Multivariate random vectors; Shovel-truck simulation
International Standard Serial Number (ISSN)
Article - Journal
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01 Sep 2016