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Hybrid genetic algorithm for test bed scheduling problems

机译:混合遗传算法解决试验台调度问题

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In this paper, we address the scheduling problem for a heavy industry company which provides ship engines for shipbuilding companies. Before being delivered to customers, ship engines are assembled, tested and disassembled on the test beds. Because of limited test bed facilities, it is impossible for the ship engine company to satisfy all customers' orders. Therefore, they must select the orders that can be feasibly scheduled to maximise profit. An integer programming model is developed for order selection and test bed scheduling but it cannot handle large problems in a reasonable amount of time. Consequently, a hybrid genetic algorithm (GA) is suggested to solve the developed model. Several experiments have been carried out to demonstrate the performance of the proposed hybrid GA in scheduling test beds. The results show that the hybrid GA performs with an outstanding run-time and small errors in comparison with the integer programming model.
机译:在本文中,我们解决了重工业公司的调度问题,该公司为造船公司提供船舶发动机。在交付给客户之前,船舶发动机要在测试台上进行组装,测试和拆卸。由于测试台设备有限,船舶发动机公司无法满足所有客户的订单。因此,他们必须选择可以合理安排的订单以使利润最大化。开发了整数编程模型用于订单选择和测试台计划,但它不能在合理的时间内处理较大的问题。因此,提出了一种混合遗传算法(GA)来解决所开发的模型。已经进行了一些实验来证明所提出的混合遗传算法在调度测试台上的性能。结果表明,与整数规划模型相比,混合遗传算法具有出色的运行时间和较小的误差。

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