关键词: 轴-辐式网络, 支线船舶调度, 非线性规划模型, 遗传算法, 多智能体进化算法

Abstract: With the increasing competition in the shipping market and the development of large-scale container ships,more and more shipping enterprises choose the mode of hub-and-spoke shipping network. As an important part of hub-and-spoke shipping network, the feeder network optimization problem is highly concerned by scholars. This study discusses the feeder scheduling problem considering the variable navigation speed andeconomic navigation speed,and establishes a nonlinear mixed integer programming model to minimize the total operation cost by taking into account the time window restrictions of the hub ports and the feeding ports. Themodel of a small-scale example is solved by the professional solver, and the accuracy of the model is verified. At the same time, an improved genetic algorithm is designed to solve the scheduling problem of large-scale feeder ships. In order to further improve the quality of the solution,a multi-agent evolutionary algorithm is designed. The numerical results show that the operation cost in the scenario with variable speed is lower than the operation cost in the scenario with economic navigation speed. In terms of algorithm efficiency, the convergence speed of genetic algorithm is faster,but the multi-agent evolutionary algorithm can obtain a better solution with higher accuracy.

Key words: hub-and-spoke network, containership scheduling, nonlinear programming, genetic algorithm, multi-agent evolutionary algorithm