Optimizing construction duration estimation and monitoring for public building projects in Addis Ababa through an integrated deterministic and probabilistic conceptual model

Effective time estimation and monitoring are crucial for the success of public building projects, especially in complex environments like Addis Ababa, where project delivery methods introduce considerable uncertainties. Existing practices in Addis Ababa often lead to unreliable schedules and increased risk. This study addresses these issues by developing an integrated conceptual model that merges deterministic and probabilistic approaches to enhance schedule accuracy and reliability. The model incorporates factors such as project scope, regulatory requirements, site conditions, contractual terms, historical data, resource availability, and economic and political influences. Data was collected from clients, consultants, and project supervisors on construction duration estimation, time monitoring, and delivery system uncertainties. Key influential parameters identified include the number of buildings, regulatory approvals, government shutdowns, project locations, risk management strategies, and site conditions. The model proposes using historical data and expert judgment to establish baseline durations, which are adjusted for factors like regulatory delays and site-specific conditions. It employs probabilistic methods like Monte Carlo simulations and PERT to account for variability. The integrated approach combines these results to provide a comprehensive project duration estimate and includes a roadmap for implementation in R and Python, validated using MAE, RMSE, and R2 metrics.