###### Abstract
Although the Yangtze River Economic Belt has achieved integrated transportation between the river and sea, coordination between multiple departments, such as inspection and quarantine, maritime affairs, border inspection, and port and shipping, remains difficult, and the comprehensive formation of a convenient customs clearance service environment has not yet been achieved [11]. In practice, seagoing ships selected for inspection upon arrival at port undergo inspections before and after loading and unloading operations. This contrasts sharply with domestic trade ships exempt from such procedures. Consequently, scheduling cannot be uniform for all ships. Ignoring seagoing ship inspection arrangements impacts ship waiting and departure times, potentially affecting multimodal transportation's economy and convenience. Current ship scheduling research primarily focuses on micro-level analyses within specific daily time periods. While some researchers use random simulations of ships arriving early or late, there are still gaps in longer-term planning research [12], limiting the continuity of the scheduling plan. Most scholars use operations research solvers, traditional optimization algorithms (e.g., simulated annealing or mountain climbing), or mathematical optimization algorithms for ship scheduling. However, these models face many constraints, making it difficult to obtain effective solutions with solvers like CPLEX and Gurobi. Traditional algorithms often exhibit a low efficiency for complex multi-objective problems [13]. Mathematical optimization struggles with single-objective weights, finding optimal solutions under one weight at a time, leading to challenges in non-convex situations, inconsistent objective dimensions, and poor robustness. In order to address the above issues, this paper proposes a mathematical model for coordinated scheduling. First, the scheduling situation of Yangtze River ports was analyzed to identify the conditions that limit ship scheduling. Subsequently, an optimization objective function was constructed with the goals of minimizing berth deviation costs and total scheduling time while maximizing berth utilization. The scheduling model fully accounted for the impacts of berth preference costs and customs inspection factors. Finally, by integrating the initial population and dynamically adjusting crossover and mutation probabilities,the conventional NSGA-III algorithm was optimized. Then, an experimental validation was conducted with a planning period of 7 days and the results showed that, compared to the port's original scheduling scheme, the optimized NSGA-III algorithm improved the three objective values by 30.81%, 13.73%, and 12.11%, respectively. Additionally, berth deviation costs were reduced by CNY 95 and CNY 362 compared to the NSGA-III and NSGA-II algorithms. The total scheduling time was also reduced by 274.3 min and 1991.22 min, respectively. Berth utilization rates were slightly improved compared to both algorithms. The remainder of this paper is organized as follows: Section 2 discusses our port background and problem statement. Section 3 introduces the optimized scheduling model. Section 4 discusses the optimized NSGA-III algorithm. Section 5 presents the experimental setup and results. Section 6 provides the discussion and conclusion.