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针对集装箱船配载优化中的Bay位优选问题,提出以倒箱量、重心横向偏移和初稳性高为目标,以箱位与Bay位的一致和Bay位重量为约束条件的数学模型,提出一种多目标离散粒子群算法(MODPSO)求解之,得到该算法优化后的Pareto解集和Pareto解迭代过程中的变化趋势图,为集装箱船配载问题提供多种方案以供备选,从而达到在提高集装箱船装载效率、节约装载成本和时间、使集装箱船获得稳定航行状态等目标间取得更好平衡的目的。
Aiming at the optimization of bay position in container ships, a mathematical model is put forward, which aims at the optimization of bay position, lateral shift of center of gravity and high initial stability, with the coincidence of bay position and bay position and Bay weight. A multi-objective discrete particle swarm optimization algorithm (MODPSO) is proposed to solve the problem. The optimized trend of Pareto solution set and Pareto solution iteration process is obtained, which provides a variety of options for container ship loading. So as to achieve the goal of achieving a better balance between the objective of enhancing the loading efficiency of container ships, saving the loading cost and time, and enabling the container ships to obtain a steady state of navigation.