Estimating Construction Project Duration and Costs upon Completion Using Monte Carlo Simulations and Improved Earned Value Management

Abstract

Earned value management (EVM) is widely used when monitoring and estimating operations related to construction projects. As the scope and complexity of construction projects expand, traditional EVM is sometimes ineffective and even results in conclusions that are contrary to the actual situation. Additionally, the estimate produced by EVM is a deterministic value that does not account for the uncertainty of activities involved in a construction project. This study proposes an estimation approach that combines an improved EVM, critical path method (CPM), program evaluation and review technique (PERT), and Monte Carlo simulation (MCS). The contribution is threefold. Firstly, a path-based schedule measurement approach is described using network diagrams and CPM to capture the logical relationships among activities. Secondly, the resource input categorizes activities to improve the accuracy of the duration and cost estimates. The remaining duration and cost will be estimated based on the execution performance of the activities in the same category. Thirdly, PERT and MCS approaches are used to reveal the uncertainty of estimates upon completion by replacing a deterministic value with a possible completion range. An experimental research study was used to apply the proposed approach. The result displayed that the commercial expansion project faced serious schedule delays and cost overruns. Based on the result, the project manager should focus highly on activities J, H, and G (in order of priority) and take corrective actions. In conclusion, the proposed approach demonstrates good performance when identifying deviations, estimating precise results, and determining the importance (priority) of activities that need to be controlled.