Activity network scheduling and early cost estimation of construction projects under uncertainty: A risk analysis based modeling approach

It is not sufficient in hard and competitive construction sector conditions to evaluate the construction activity schedules that are affected widely by risks and uncertainties with well-known deterministic or probabilistic methods such as the Critical Path Method (CPM) or Program Evaluation and Review Technique (PERT). These approaches neglect the uncertainty or correlation effect. Uncertainties and risk-factors not only affect the activity schedules but also affect the construction costs. Hence, the actual costs, likewise the activity durations, generally deviate from the estimated costs in favorable or adverse direction. Therefore, not only scheduling the construction activities and estimating the construction costs but also the analysis of the uncertainty effect over the schedules and early estimated costs in an efficient manner is required.In this context, the aim of this study is to evaluate the uncertainty effect on construction project activity network schedules and estimated costs, and to develop simulation-based schedule and cost risk analysis models that can be used for the uncertainty evaluation of construction projects. Two new simulation-based schedule risk models, Correlated Schedule Risk Analysis Model (CSRAM) and Correlated Fuzzy Schedule Risk Analysis Model (CFSRAM), are proposed to examine construction activity networks under uncertainty when activity durations and risk factors are correlated, and a new simulation-based cost risk model, Correlated Cost Risk Analysis Model (CCRAM), is introduced to analyze early construction costs under uncertainty when the costs and risk-factors are correlated. Correlation has been captured indirectly and qualitatively by these models. The models are capable of providing risk-factor sensitivity information to support schedule management and cost management. Probability and fuzzy set have been the main mathematical theories in developing the models? theoretical logic.The efficiency of the models has been evaluated through hypothetical and real applications in the study. The findings of these applications show that CSRAM, CFSRAM and CCRAM operate well and produce realistic results compatible with the theoretical expectancies.