A Cost Estimation Method Considering Uncertainties Based On Monte Carlo Simulation

Abstract

In this study, various methods for examining the internal and external risks dealing with cost estimation are reviewd. After selecting the most appropriate approach, the influencing factors are collected using the questionnaire-based method. Then, its consistency is measured with Cronbach's alpha coefficient. The prioritization of risks is conducted through the decision-making trial and evaluation laboratory (DEMATEL) method, wherein the effectiveness and probability of each case are evaluated. Next, the probability of occurrence and the impact weight of each risk are extracted by applying common probability distribution functions to the available data. Then, sensitivity analysis of the number of random variables in the Monte Carlo method is conducted. The probability of environmental risks occurring is highest, approximately 25% to 80%, while respondents estimate inflation and financial risks with greater certainty. Additionally, the impact weight of each risk is highest for inflation risk, 40%, and lowest for financial risk, 15%. Finally, the additional cost is calculated using the Monte Carlo method. The results indicate that the estimated cost of the entire project is 1.83 times the initial estimate due to risks. When compared to the actual costs of three projects located in Karaj city, the difference is at most 10%. At the same time, the initial estimate significantly deviates from reality. Therefore, the Monte Carlo simulation, which accounts for the uncertainty of risks, can be considered a suitable method for project cost estimation.