Abstract: Water-water transshipment of containers is an economical and efficient waterway transportation mode. To effectively reduce the inter-terminal transit cost of transshipment containers in large transshipment hub ports under water-water transshipment scenarios, a multi-objective optimization based multi-terminal transfer port berth resource allocation scheme was proposed. Considering the constraints such as the safe berthing time and distance of vessels and the container-vessel matching relationship, a multi-objective mixed integer programming model was established to minimize the time cost of vessels in the port and the transportation cost of transshipment containers between terminals. The proposed model was solved by NSGA-Ⅱ algorithm to obtain multiple sets of ship berthing and transshipment containers transportation plans under different scales. It is shown that the proposed algorithm can obtain multiple sets of Pareto frontier solutions, providing multiple optimization scenarios for port operators and shipping lines. And the results show a trend of a corresponding reduction in the cost of transshipment transport between transshipment container terminals at the expense of an increase of the time cost of vessel in port. Compared to traditional scheduling schemes based on minimum time cost, the proposed scheduling scheme effectively reduces the operating costs of vessels berthing in multiple terminals, and it has good robustness under uncertain scenarios. Specifically, it can reduce the total operating cost by 38.25% to 69.48% under different vessel scales. Through the time cost loss of ships in port to a lesser extent, the inter-terminal transshipment costs of transshipment containers can be significantly reduced, providing reference for berth allocation and inter-terminal transportation integration optimization for water-water transshipment.

Key words: traffic and transportation engineering; continuous berth allocation problem; NSGA-II; multiple terminals; water-water transshipment

摘要： 集装箱的水水中转是一种经济高效的水路运输模式，为有效降低水水中转下中转箱在大型转运枢纽港的码头间中转成本，提出了基于多目标优化的多码头转运港泊位资源分配方案。该方案考虑了船舶安全靠泊时间与距离以及中转箱与船舶的匹配关系等约束，建立了多目标混合整数规划模型，旨在最小化船舶在港时间成本与中转箱码头间运输成本；使用非支配排序遗传算法(NSGA-Ⅱ)对模型进行求解，得到了多组不同规模下的船舶靠泊与中转箱转运方案。研究表明：该算法能够得到多组帕累托前沿解，为港口运营商和船舶公司提供多个优化方案，以船舶在港时间成本的增长为代价，中转箱码头间中转运输成本呈减少的趋势；相较于基于最小时间成本的传统调度方案，提出的调度方案能够有效降低多码头下船舶靠泊的运营成本，同时在不确定情景下具有良好的鲁棒性；具体而言，在不同船舶规模下，能够减少作业总成本的38.25%~69.48%；以较小程度的船舶在港时间成本损失为代价，明显减少中转箱的码头间中转成本，为水水中转下的泊位分配和码头间运输集成优化提供参考。

关键词: 交通运输工程；连续泊位分配问题；非支配排序遗传算法；多码头；水水中转