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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >Development of a maritime transportation planning support system for car carriers based on genetic algorithm
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Development of a maritime transportation planning support system for car carriers based on genetic algorithm

机译:基于遗传算法的汽车承运人海上运输计划支持系统的开发

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摘要

Recently, the port logistics market is rapidly expanding, along with the active maritime trade. To adjust to this trend and gain a competitive advantage, competition among shipping companies at home and abroad has intensified, and many efforts are being made for the improvement of customer services and cost saving. In particular, car carriers transporting more than 80% of total car import/export volume must quickly make efforts to reduce transportation costs. Much research has been conducted to improve the efficiency of maritime transportation, but studies on car carriers, which are given relatively less importance, have been lacking. The car carrier's transportation planning is similar to the vehicle routing problem, but it is much more complicated in that cars and cargo are prepared at different points in time, and cargo can be loaded not only at the departing port but also at other ports. Therefore, in an effort to solve the problem, this study has developed a meta-heuristic algorithm based on a genetic algorithm, and we have succeeded in developing a maritime transportation planning support system with the algorithm, thus making it possible to prepare various alternatives, evaluate them, and consequently support user's decision making.
机译:近年来,随着活跃的海上贸易,港口物流市场正在迅速扩大。为了适应这种趋势并获得竞争优势,国内外船运公司之间的竞争加剧了,为改善客户服务和节省成本做出了许多努力。特别是,运输量占汽车进出口总额80%以上的汽车运输商必须迅速努力降低运输成本。为了提高海上运输的效率,已经进行了许多研究,但是缺乏对汽车载具的研究,这些研究相对不那么重要。汽车承运人的运输计划与车辆路线问题相似,但是要复杂得多,因为汽车和货物是在不同的时间点准备的,货物不仅可以在出发港口装载,还可以在其他港口装载。因此,为解决该问题,本研究开发了一种基于遗传算法的元启发式算法,并且我们成功开发了具有该算法的海上交通规划支持系统,从而有可能准备各种替代方案,对它们进行评估,从而支持用户的决策。

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