In order to minimize the influence of construction for airport operation, the construction method of closing part of time or some pavement without stopping is usually used by the airport pavement maintenance office. Therefore, it is necessary to consider the key objectives of construction management, such as quality, duration and safety, and carry out a research on construction organization and management in the maintenance and repair of airport pavement. A multi-objective optimization model was proposed for the non-stop construction organization of airport pavements, focusing on the construction period within airport pavement maintenance management. The construction process was emphasized and functional relationships among cost, quality, and construction time were established to quantify each objective scientifically. Moreover, an optimization model was developed, incorporating the construction window period as a constraint and leveraging the closure of nighttime hours to facilitate uninterrupted construction without disrupting navigation. The approach ensures efficient non-stop construction of airport pavements. In the model, a triple objective optimization strategy was employed, aiming to minimize duration and cost while maximizing quality level. To solve the model, the performance of multiple objective particle swarm optimization (MOPSO), nondominated sorting genetic algorithm-Ⅱ（NSGA-II), and NSGA-Ⅲ algorithms was compared under the 3D objectives. The results demonstrate that all three algorithms show commendable performance in solving the concave optimization problem DTLZ2, with NSGA-Ⅲ notably outperforming the others in tackling the three-dimensional optimization problem. The capacity of the model to further optimize construction management objectives, while fully adhering to construction constraints, was verified, which provided a decision-making framework for construction organization and management in airport pavement maintenance, catering to diverse requirements.