Time and cost with monte carlo simulation predicting uncertainty

In this thesis, 68 input parameters that have the potential to affect the duration and cost of construction projects are identified and their effects on construction duration and cost are analyzed by Monte Carlo Simulation. The simulation was used to estimate construction time and cost by generating 25,000 random values for each parameter. The input parameters consist of uncertainty in activity durations, personnel, construction equipment and material costs. Linear work schedule method was applied to generate the work schedule. The parameters were modeled in accordance with the uncertainty distributions determined according to the normal distribution and the construction time and cost were analyzed 25,000 times by making random matches for each parameter. As a result of the simulation, the construction cost was estimated as 69,476,481.63 TL ± 4,695,718.72 TL and the construction period as 472.47 ± 36.89 days for a 9-story building project. Two different simulation scenarios were created with and without considering the time value of money. The parameters that have the most impact on construction time and cost are highlighted. This study provides an effective method to quantify the effects of uncertainty in construction projects and improve risk analysis.