Estimating Project Completion Time with Monte Carlo Simulation

Abstract

Risk and uncertainty are factors that construction project managers have been increasingly had to deal with. Project completion time is one of the areas where the expected time is often underestimated or shorter than the actual completion time. Monte Carlo simulation is a widely used simulation technique in modeling a process that is difficult to predict due to its random variables. This study provides a practical way to use Monte Carlo simulation to simulate a project using functions available in a spreadsheet application. A project with five activities was simulated 2000 times using minimum, maximum, and expected duration. The mean, mode, and median simulation results were then plugged into their respective precedence diagram networks to compare them. The precedence diagram computations found that mean, mode, and median project completion times were longer than the initially expected completion time. The mean, mode, and median were 50, 53, and 48 days, respectively, which were 8, 11, and 6 days longer, respectively, than the 42 days initially expected. The study showed that the Monte Carlo simulation could assist the project manager in planning a project schedule that deals with risk and uncertainty more realistically.

Scheduling The Construction of Low-Income Community Houses in Palu City Using the Probabilistic Duration Method

“…In Monte Carlo Simulation, the estimation of activity durations involves using a random variable [9,10] that falls within the range of minimum and maximum durations. The multiplicative congruential method is a commonly used mathematical technique for generating random numbers ranging from 0 to 1 [11].…”