An Advanced Metaheuristic Framework for Time–Cost–Quality Optimization in Complex Construction Projects

Contemporary construction projects demand a holistic management approach that does not balance time and cost only but preserve quality under uncertain conditions also. Traditional methods often emphasize time–cost trade-offs, overlooking the intricate link between task sequencing and quality outcomes. To address these limitations, this paper introduces a novel optimization framework combining the multi-objective sea-horse optimizer (MOSHO), the root assessment method (RAM), and fuzzy logic, specifically designed for time–cost-quality trade-off (TCQT) scenarios. The proposed model was tested against established algorithms—MOSGO, MOSOS, and NSGA-III on real-world construction data. Results demonstrate that the integrated MOSHO-RAM-Fuzzy logic approach outperforms the conventional mentioned techniques. This consistently generates well-distributed solutions that effectively reconcile cost efficiency, project duration, and product quality. This integrated model also serves as a robust decision-support tool in the context of involving multiple execution alternatives, particularly suited to the scheduling phase of large-scale projects where uncertain parameters significantly impact construction project outcomes.