###### Abstract  
Efficient coordinated scheduling has long been a focal point in port research, complicated by the diverse optimization goals dictated by different port characteristics. This study focuses on Yangtze River ports, exploring coordinated scheduling amidst river-sea intermodal transportation. Our research aims to reduce both deviation costs and shorten the total scheduling time for ships, while maximizing berth utilization rates for ports. Initially, we analyzed the operational realities of Yangtze River ports and waterways. Subsequently, we innovatively introduced three key factors influencing scheduling: berth preferences, seagoing ship inspections, and planning cycles. Finally we proposed the optimized Non-dominated Sorting Genetic Algorithm III (NSGA-III). Evaluating the model using a seven-day dataset of vessel activities at Yangtze River ports revealed significant improvements: the optimized NSGA-III enhanced objective values by 30.81%, 13.73%, and 12.11% compared to the original scheduling approach, surpassing both conventional NSGA-III and NSGA-II algorithms. This study underscores the model's efficacy in not only reducing operational costs through optimized ship and berth sequencing but also in enhancing clearance efficiency for relevant authorities. waterway scheduling; berth allocation; preferred berth; berth utilization; optimized NSGA-III +
Footnote †: journal: Applied  
initialization population, two-point crossover, and single-parent crossover optimization strategies, resulting in a reduction of 68.5% and 29.2% in the total waiting time and total scheduling time, respectively, compared to the original NSGA-II. [PERSON] [6] developed a mixed-integer linear programming model for one-way waterway ports and used an adaptive large neighborhood search algorithm with a rolling plan for dual waterway ports to address the issue of large ships occupying the entire waterway. A two-stage stochastic programming model was also constructed and solved using Benders decomposition and heuristic algorithms, considering various uncertainties. [PERSON] [7] developed a Markov decision process model for berth allocation and quay crane scheduling, considering quay loading capacity, cargo types, and switch setup times. A greedy insertion offline algorithm was used to significantly reduce waiting times, enhancing port efficiency and flexibility. [PERSON] [8] considered factors such as tides, entry and exit time periods, and preferred berths to establish a 0-1 integer linear programming model using the sum of the berth deviation cost and ship demurrage cost as optimization objectives to determine the entry and exit times and berthing positions of each ship. [PERSON] [9] investigated the berth allocation problem arising from uncertain operation times due to fluctuations in the total number of containers. It aimed to minimize the total deviation cost between the planned and expected berthing times of vessels. A comprehensive expanded robust optimization framework was developed, and a column-and-constraint generation algorithm was employed for solving it. Compared to first-come-first-served and rolling horizon planning methods, this framework significantly improves the expected costs within an acceptable computational time. Although existing studies have considered the coordinated scheduling of waterways and berths from different perspectives,there are still some issues: Many scholars have overlooked berth preferences. Berth and warehouse locations are fixed, ports must minimize the operational time and workload while ships must quickly complete loading and unloading at preferred berths to shorten shipping schedules. Thus, ignoring berth preference imposes a burden on both parties [10].