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Multiobjective Approaches for the Ship Stowage Planning Problem Considering Ship Stability and Container Rehandles

机译:考虑船舶稳定性和集装箱装卸的船舶配载计划问题的多目标方法

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The ship stowage planning problem (SSPP) is a very complex and challenging problem in the logistics industries because it affects the benefits of both shipping lines and port terminals. In this paper, we investigate a multiobjective SSPP, which aims to optimize the ship stability and the number of rehandles simultaneously. We use metacentric height, list value, and trim value to measure the ship stability. Meanwhile, the number of rehandles is the sum of rehandles by yard cranes and quay cranes and all necessary rehandles at future ports. To solve this problem, a variant of the nondominated sorting genetic algorithm III (NSGA-III) combined with a local search component is proposed. The algorithm can produce a set of nondominated solutions. Decision makers can then choose the most promising solution for practical implementation based on their experience and preferences. Extensive experiments are carried out on two groups of instances. The computational results demonstrate the effectiveness of the proposed algorithm compared to the NSGA-II and random weighted genetic algorithms, especially when it is applied in solving the six-objective SSPP.
机译:船舶积载规划问题(SSPP)在物流行业中是一个非常复杂且具有挑战性的问题,因为它影响着航运公司和港口码头的利益。在本文中,我们研究了一种多目标SSPP,旨在同时优化船舶稳定性和重新处理数量。我们使用偏心高度,列表值和纵倾值来衡量船舶的稳定性。同时,重新处理的数量是院子起重机和码头起重机的重新处理的总和,以及将来港口的所有必要重新处理的总和。为了解决这个问题,提出了一种非支配排序遗传算法III(NSGA-III)与局部搜索组件相结合的变体。该算法可以产生一组非支配解。然后,决策者可以根据他们的经验和偏好选择最有希望的解决方案用于实际实施。在两组实例上进行了广泛的实验。计算结果表明,与NSGA-II算法和随机加权遗传算法相比,该算法是有效的,尤其是在求解六目标SSPP时。

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