A non-unit repetitive construction project scheduling with uncertainties

Repetitive construction project scheduling is a crucial aspect of modern construction project management. This study focuses on the scheduling of non-unit repetitive construction projects with non-serial activity groups, multiple crews, flexible or fixed sequences, and under correlated uncertainties. An integrated model has been developed by combining novel algorithms for non-unit repetitive project scheduling and probabilistic scheduling with correlated uncertainties, alongside evolutionary optimization algorithms (e.g., Differential Evolution (DE), Firefly Algorithm (FA), and the DEFA hybrid). The proposed model is capable of generating near-optimal or optimal schedules with minimal project duration under uncertainties and constraints of work continuity, thereby enhancing the reliability and efficiency of scheduling across various examples. This advancement provides project planners with a valuable tool to manage the complexities of repetitive construction project scheduling under uncertainty. Furthermore, the study lays the groundwork for future research in high-performance computing to enhance optimization techniques and broaden the model's application in construction. •Introduces an integrated model for optimizing Non-Unit Repetitive Construction Projects.•Incorporates optimal scheduling with multiple crews, non-serial activity groups, and flexible or fixed sequences.•Utilizes probabilistic methods such as PERT, Triangular, and Normal distributions for random activity durations.•Examines correlated uncertainties within the same activity group, enhancing project reliability.•Validates the proposed model through four comprehensive case studies, demonstrating improved reliability in scheduling.