Probabilistic simulation for developing likelihood distribution of engineering project cost

Inaccurate early project cost estimates can eliminate investment benefits. This study focuses on assisting estimators who are attempting to enhance the accuracy and reliability of engineering project cost in the pre-conceptual stage. This aim has recently garnered the attention of the transportation communities. Data from the Texas Department of Transportation (TxDOT) were utilized to develop an alternative approach that aids decision makers in terms of probability and confidence level. The proposed procedure comprises heuristic and practical simulation models that can be employed to calculate the probabilistic costs of highway bridge replacement projects. The simulation models utilize independent, correlated, and Latin Hypercube sampling approaches that incorporate major work items, roll-up work items, and project-level engineering contingencies. Cumulative distribution functions (CDFs) are then developed as a user-friendly chart for decision makers and these CDFs can be used to assess project risks during the pre-conceptual stage. Trial runs using these estimating procedures generate reliable pre-conceptual estimates. Additionally, these procedures can be extended to other project types along with programming techniques for developing an engineering project cost decision support system.