Global time optimization method for dredging construction cycles of trailing suction hopper dredger based on grey system model

The efficient operation of trailing suction hopper dredgers can reduce equipment operation time and energy consumption, accelerate overall construction, reduce workload and material resource usage, and lower construction costs. Based on an in-depth analysis of the dredging construction optimization problem, the overflow loss prediction and a loading cycle optimization method based on the loaded earth curve are proposed in this study. The loading cycle optimization method is divided into three stages. In the first stage, statistical learning and machine learning methods are used to predict and analyze the loaded earth data by describing the time scale of the loaded earth data, and the grey system prediction model was selected for the subsequent developments. In the second stage, by analyzing the loaded earth curve prediction model, the concept of overflow loss rate and its predictive calculation method is proposed. In the third stage, combined with the loaded earth curve prediction model, a global time geometric coordinate optimization model of the loading cycle is proposed to avoid the power and time waste caused by excessive overflow loss. A channel dredging project in Tianjin Port was taken as an application example to verify the applicability of the proposed optimization method and optimize the construction work efficiency.