Development of discrete opposition-based NSGA-III model for optimizing trade-off between discrete time, cost, and resource in construction projects

Balancing discrete time, cost, and resource allocation poses a significant challenge in construction projects due to their inherent conflicts. The competitive nature of the construction market underscores the importance of optimizing trade-offs among these objectives for successful project completion. To address the complexities and limitations of existing models, this paper presents a discrete time-cost-resources trade-off (DTCRT) optimization framework utilizing the opposition-based non-dominated sorting genetic algorithm (OBNSGA III), in which opposition-based learning (OBL) is used for generating the initial population. The proposed model accommodates multi-mode project activities with varying resource requirements. A case study application demonstrates the efficacy of proposed approach in generating the Pareto-optimal solutions. Comparative analysis against existing techniques validates the effectiveness of proposed method. Additionally, trade-off plots and an a priori decision-making tool are provided to facilitate selection among the generated solutions by project stakeholders.