PROBABILISTIC SCHEDULING OF RESIDENTIAL CONSTRUCTION USING MONTE CARLO SIMULATION
DOI:
https://doi.org/10.55766/sujst11572Keywords:
Construction Project Scheduling, Construction Uncertainty, Monte Carlo Simulation, Precedence Diagram Method, Residential Building Project, Risk ManagementAbstract
The Precedence Diagram Method (PDM) relies on deterministic activity times to calculate the Total Project Duration (TPD), a characteristic that inherently limits its predictive accuracy. To address this limitation, the present study integrates Monte Carlo Simulation (MCS) with conventional PDM calculation to predict the TPD of a luxury housing project. Initially, the critical path was identified through the conventional PDM approach. Subsequently, MCS was applied, running 10,000 iterations under the assumption of a normal distribution for all activity durations. The choice of normal distribution is grounded in Central Limit Theorem (CLT), which is efficient for aggregate project level. The TPD for each iteration was recorded, thus generating a probability distribution for project completion time. The deterministic PDM analysis initially yielded a TPD of 420 days. In contrast, the MCS approach produced a mean TPD of 397 days (a 23-day reduction) and revealed only a 45.6% probability of meeting the original deterministic completion date. By incorporating the inherent variability of activity durations, the MCS-derived TPD provides significantly more realistic timeline projections and probabilistic insights. This study demonstrates the potential of MCS in residential construction projects, which remains underutilized in Thailand. Consequently, this research demonstrates a tangible advancement over conventional, deterministic network planning methodologies.
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