The construction of underground engineering in urban areas involves a vast array and substantial quantity of construction machinery, which can pose a significant challenge of noise pollution during construction. To address this issue, a noise management method based on optimizing the configuration of construction machinery was presented. Firstly, the primary noise sources during construction were analyzed, and a noise source model was established. Secondly, the health effects induced by exposure to construction noise were analyzed, and the exposure-response formula was determined. Finally, a multi-objective optimization model for the configuration of construction machinery was developed, which considered the health damage cost caused by construction noise, as well as constraints on construction period, cost, and quality. To demonstrate the feasibility and practicality of the proposed method, a case study of deep excavation construction in a tunnel engineering project in Wuhan was presented, and a hybrid algorithm combining genetic algorithm and improved quantum particle swarm optimization algorithm was utilized to solve the optimization model. The results indicate that the proposed method can reduce construction noise while meeting the requirements for construction efficiency, and thus has significant potential for practical implications