Optimizing construction time, cost, and quality: a hybrid AHP-NSGA-II optimization model

In construction projects, the simultaneous optimization of time, cost, and quality remains a paramount challenge due to their inherent trade-offs. This paper provides an innovative approach to address this challenge through a hybrid optimization model integrating Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Analytical Hierarchy Process (AHP). By considering diverse alternatives for each activity, along with their respective time, cost, and quality impacts, developed model quantitatively assesses project quality while minimizing time and cost. Utilizing pairwise comparisons within AHP, the relative weights of activities and quality indicators are determined, providing a structured framework for decision-making. Subsequently, NSGA-II is used to identify Pareto-optimal solutions and offer project managers a variety of trade-off options between time, cost, and quality. A case study application and results comparison demonstrate the effectiveness of developed model and reveal its ability to generate efficient project completion strategies. By facilitating better understanding and management of the time-cost-quality trade-off (TCQT), this study contributes to enhancing project efficiency and stakeholder satisfaction.