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A drayage problem considering real-time vehicle position knowledge by using genetic algorithm

机译:考虑遗传算法的实时车辆位置知识的拖曳问题

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The scheduling of transportation systems has traditionally been done once a day. At beginning of a working day, the planner establishes which tasks will be carried out by each vehicle. Then, traffic jam, breakdown and any unexpected problem will cause delays on our timetable. In this paper, we propose to use real-time vehicle position knowledge to solve this problem. So, the planner is permanently enabled to reallocate tasks as the problem conditions change. As both drayage problem is a NP-Hard problem and a high-speed procedure is required, exact methods are not computationally feasible. So, a genetic algorithm has been implemented to perform the problem described.
机译:传统上,运输系统的调度通常每天进行一次。在工作日开始时,计划者确定每辆车将执行哪些任务。然后,交通拥堵,故障和任何意外问题都将导致我们的时间表延迟。在本文中,我们建议使用实时车辆位置知识来解决此问题。因此,计划程序将永久启用,以便在问题条件发生变化时重新分配任务。由于两个拖曳问题都是NP-Hard问题,并且需要一个高速过程,因此精确的方法在计算上是不可行的。因此,已经实现了遗传算法来执行所描述的问题。

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