This paper investigates a novel extension of the berth allocation problem (BAP), which mainly determines berths and times for arriving vessels. Most previous studies on the BAP do not consider a cooperative environment among liner carriers. This paper proposes a berth assignment and allocation problem considering cooperative liner carriers (BAAP), which integrates the BAP with the berth assignment problem and the liner clustering problem (LCP). The LCP addresses how to group a number of liner carriers into various liner clusters, and the berth assignment problem aims to assign proper number of berths for serving vessels of various liner clusters. For solving our proposed problem, we develop a two-stage optimization method. In stage I, a mixed-integer nonlinear programming (MINLP) model is constructed to formulate our BAAP with given liner clusters, integrating the BAP with the berth assignment problem. According to the results obtained in stage I, a decision model based on cooperative game theory is presented to solve the LCP in stage II. A genetic algorithm framework embedded with a mixed-integer linear programming solver (CPLEX) is designed to solve the MINLP model constructed in stage I. The LCP in stage II can be solved by using the enumeration method. Experimental results are provided to validate the efficiency and effectiveness of our models and algorithm.

本文研究了泊位分配问题 (BAP) 的一种新扩展，该问题主要确定到达船舶的泊位和时间。大多数以前关于 BAP 的研究都没有考虑班轮承运人之间的合作环境。本文提出了一种考虑合作班轮承运人（BAAP）的泊位分配问题，将BAP与泊位分配问题和班轮聚类问题（LCP）相结合。LCP解决了如何将多个班轮运输船组合成不同的班轮集群，泊位分配问题旨在为不同班轮集群的船舶分配适当数量的泊位。为了解决我们提出的问题，我们开发了一种两阶段优化方法。在第一阶段，构建了一个混合整数非线性规划（MINLP）模型，以用给定的线性集群制定我们的 BAAP，将 BAP 与泊位分配问题相结合。根据第一阶段得到的结果，提出了一种基于合作博弈论的决策模型来解决第二阶段的LCP问题。设计了嵌入混合整数线性规划求解器（CPLEX）的遗传算法框架来求解第一阶段构建的MINLP模型。第二阶段的LCP可以使用枚举法求解。提供实验结果以验证我们的模型和算法的效率和有效性。设计了嵌入混合整数线性规划求解器（CPLEX）的遗传算法框架来求解第一阶段构建的MINLP模型。第二阶段的LCP可以使用枚举法求解。提供实验结果以验证我们的模型和算法的效率和有效性。设计了嵌入混合整数线性规划求解器（CPLEX）的遗传算法框架来求解第一阶段构建的MINLP模型。第二阶段的LCP可以使用枚举法求解。提供实验结果以验证我们的模型和算法的效率和有效性。