An Analytic Model Combining Monte Carlo Simulation and PSO in Estimating Project Completion Probability of Project Durations and Costs

Project uncertainties are always the reason of project delay or budget overrun. Especially in tight schedule or project crashing, it is hard to balance both project duration and costs. Past research focused on the optimal schedule and costs, without knowledge of its on-time, within-budget completion risk. This research provides an analytical model by first using PSO heuristic algorithm to find the minimum project costs under time constraint. Monte Carlo Simulation is then implemented to build a completion probability table of time/cost combinations. The time and cost from PSO method is compared with the probability matrix. An analysis is provided as a demonstration.