PVA simulation with Monte Carlo

It performs PVA simulations on the basis of analyses carried out by multiple decisiion-makers

The script is employed to simulate a large number of data samples comprising performance indexes which concern the phases of an industrial process. The underpinning methodology is described in:
Borgianni Y., Cascini G., Rotini F.: “Process Value Analysis for Business Process Re-engineering”, Proceedings of IMechE, Part B: Journal of Engineering Manufacture, 224(2), 2010, pp. 305-327.

The following variables have to be changed in order to fit a specific case study, containing nCR product attributes and nphases business process phases:
PHA: name of the phases
avgCS: nCR-sized vector containing mean values of CS indexes
varCS: nCR-sized vector containing variances of CS indexes
avgCD: nCR-sized vector containing mean values of CD indexes
varCD: nCR-sized vector containing variances of CD indexes
avgk: nCR × nphases matrix containing mean values of k’ij coefficients; each row is separated by semicolons
vark: nCR × nphases matrix containing variances of k’ij coefficients; each row is separated by semicolons
avgres: nphases-sized vector containing mean values of resource ratios
res_vary: nphases-sized vector containing variances of resource ratios