Monte Carlo Simulation - Stochastic uncertainty propagation through MCDM model

Overview

Monte Carlo Simulation - Stochastic uncertainty propagation through MCDM model

Output

robustness score, higher is better

Data

Crisp, complete numeric matrix

Size

2+ alternatives, 3-12 criteria works best

Used for

Sensitivity analysis, uncertainty quantification

How it works

1. 1

   Validate inputs for monte-carlo-simulation.

   $${\hat{r}}_i=\frac{1}{N}\sum _{k=1}^{N}1[{\text{rank}}_i^{(k)}=r]\forall r(\text{rank acceptability index})$$

   Metropolis 1949, (pending PDF page verification)

Look elsewhere when

Assumptions to verify

• A base ranking method is selected
• Computational budget for repeated runs

Edge cases and pitfalls

• Applying MONTE-CARLO-SIMULATION without verifying this assumption.

  Requirement: A base ranking method is selected

• Applying MONTE-CARLO-SIMULATION without verifying this assumption.

  Requirement: Computational budget for repeated runs

• Using MONTE-CARLO-SIMULATION when: Quick analysis needed → defer robustness check.

  An alternative method is recommended in this situation.

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