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Berth-Crane Allocation Model and Algorithm of Container Berths in the Uncertain Environment

机译:不确定环境中容器泊位的泊位分配模型与算法

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According to the randomness of the vessel's arrival time and handling time, the establishment of a randomly-oriented environment container berths— crane allocation model, the optimizing goal is to minimize the average shipwaiting time. Taking into account the complexity of the model solution, this paper offers the design of an improved genetic algorithm to reduce the searching space, and according to the characteristics of the optimal solution. With testing example to verify that the model can simulate decision-making environment of berths— crane allocation problem and reflect the decision-maker's attitude toward risks and preferences. The algorithm can gain a stable and satisfactory solution within the operating time.
机译:根据船舶到达时间和处理时间的随机性,建立一个随机环境集装箱泊位分配模型,优化目标是最大限度地减少平均送货时间。考虑到模型解决方案的复杂性,本文提供了改进的遗传算法设计,以减少搜索空间,并根据最佳解决方案的特性。使用测试示例来验证模型可以模拟泊位分配问题的决策环境,并反映出决策者对风险和偏好的态度。该算法可以在操作时间内获得稳定且令人满意的解决方案。

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