关键词: 水路运输, 船期恢复, 并行约束遗传算法, 集装箱班轮, 货物路由再规划

Abstract: To reduce the negative effects of schedule delays on the operational costs of liner shipping networks, this paper investigates the schedule recovery problem considering container routing replanning within the network. Three strategies are employed for schedule recovery, namely, increasing the ship speed, shortening the berthing time at the port and cancelling the call of port. These strategies underpin a mixed-integer nonlinear programming model, constructed to minimize the overall operational cost of the liner shipping network. Considering the complexity of the solution structure in the ship schedule recovery problem, a parallel constrained genetic algorithm is developed. The spatio-temporal network of liner shipping is constructed with 22 publicly available schedule data on four routes of OCEAN Alliance, and 150 examples are randomly generated to verify the effectiveness of the model and the algorithm. The results show that the proposed parallel constrained genetic algorithm exhibits robust stability and superior problemsolving capabilities in the context of ship schedule recovery. When compared to a single-ship schedule perspective, recovering disrupted schedules from a network-wide vantage point results in a lower total operational cost, with savings of approximately $37 million in certain scenarios. The initial transport plan is an important criterion for liner shipping network operations, and delays in vessel schedules can disrupt the intricate network dynamics. By adopting a network perspective approach to schedule recovery, not only are the adverse impacts of schedule changes on overall operational costs reduced, but also the continuity of the original transport plan within the liner shipping network is safeguarded.

Key words: waterway transportation, vessel schedule recovery, parallel constraint genetic algorithm, container liner, cargo re-routing