COMPARATIVE ANALYSIS OF CONSTRUCTION DURATION METHODS: DETERMINISTIC AND STOCHASTIC APPROACHES

Abstract

The article examines two fundamental approaches to determining construction duration — deterministic and stochastic. It is shown that the choice of calculation method affects not only the project schedule, but also the accuracy of time estimation, the stability of managerial decisions, time reserves, and the quality of construction progress control.  The approaches are compared in terms of input data, calculation logic, sensitivity to risks, and applicability at different stages of investment and construction projects. Particular attention is paid to the advantages of stochastic modeling under conditions of uncertainty, including the use of probability distributions, scenario analysis, and reliability assessment of results. At the same time, the limitations of this approach are considered, such as insufficient input data, high computational complexity, and the need for specialized software. The study also examines the influence of organizational and technological factors on forecasting construction duration. It is noted that modern construction projects are characterized by significant uncertainty caused by changing weather conditions, fluctuations in resource costs, instability of material supplies, labor shortages, and the need to adjust design solutions during project implementation.  In this regard, traditional scheduling methods based only on fixed normative indicators do not always ensure reliable predictions of project completion dates. It is demonstrated that stochastic methods, including PERT, Monte Carlo simulation, and network modeling, make it possible to account for random factors and develop probabilistic estimates of construction duration. These methods also improve project management by identifying the most sensitive sections of the critical path and forming appropriate time reserves. As a result, the study concludes that the combined application of deterministic and stochastic approaches is the most effective solution, where deterministic methods are used for baseline scheduling, while stochastic methods are applied for risk analysis, forecasting deviations, and improving the reliability of managerial decisions.