Incorporating Uncertainty into Project Schedule Crashing: An Algorithm

The uncertain environment in which construction projects are executed poses a challenge to project managers and planners alike as they go about planning and controlling these endeavours. Statistical and simulation models have been devised over the years to assist in estimating the time and cost of construction activities while accounting for uncertainty. However, most of these models fail to comprehensively associate these uncertainty-mindful estimates with the varied resource patterns/configurations that may undertake the work. As a result, when performing schedule crashing, one could end up with a very different strategy for project execution when accounting for all uncertainties compared to the deterministic counterpart. As such this paper presents a dynamic simulation algorithm for project schedule crashing. The devised algorithm incorporates computer simulation into the resource-time-cost triad at the activity and project levels. To perform the dynamic simulation, successive schedule simulations are created with each corresponding to a particular resource pattern/configuration that could possibly be used for executing project activities. After each simulation run is completed, parameters such as the project’s completion time and direct cost are estimated against a certain degree of confidence. The combination of resource patterns for project activities that delivers the minimum project cost is then utilized to produce the optimal-cost project schedule. The computer automated algorithm is exemplified via a simple project scenario. Results are compared to the traditional approach for least cost scheduling, which show how ignoring the uncertainty dimension could result in strategies far from being optimal