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The vehicle loading problem with a heterogeneous transport fleet

机译:异构运输车队的车辆装载问题

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As an emerging variant of the vehicle loading problem, the heterogeneous multi-type fleet vehicle loading problem in finished vehicle logistics (HVLP-FVL) is modeled and solved. The HVLP-FVL maximizes the total profit of a vehicle fleet where different models of finished vehicles result in different profits and routing costs are considered based on distance traveled. Addressing the vehicle structures, simplified geometric models of both the finished vehicle and transport vehicle are defined. The optimization considers which finished vehicle orders to transport and then makes the loading assignment to the transport vehicles. To improve the computational performance of the traditional branch and bound algorithm, an enhancement using greedy search based on oscillation analysis is proposed. A real case study is used to evaluate the effectiveness of the improved algorithm and a series of experiments are conducted over a set of finished vehicle loading problems. The results demonstrate the proposed approach has superior performance and satisfies users in practice. Contributions of the paper are the modeling and solving of a real complex problem in vehicle manufacturing logistics and a simple branch-and-bound speed up that could be used in other problem classes.
机译:作为车辆装载问题的一个新兴变体,对整车物流中的异构多类型车队车辆装载问题(HVLP-FVL)进行建模和求解。 HVLP-FVL可最大程度地提高车队的总利润,其中,不同型号的整车将产生不同的利润,并且根据行驶距离考虑路线成本。针对车辆结构,定义了成品车辆和运输车辆的简化几何模型。该优化考虑要运输的成品车辆订单,然后将装载分配给运输车辆。为了提高传统分支定界算法的计算性能,提出了一种基于振荡分析的贪婪搜索算法。实际案例研究用于评估改进算法的有效性,并针对一系列完成的车辆装载问题进行了一系列实验。结果表明,该方法具有较高的性能,并在实践中满足了用户的需求。本文的贡献在于对汽车制造物流中一个真正复杂问题的建模和求解,以及可以在其他问题类别中使用的简单的分支定界加速。

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