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Integrated Optimization of Finished Product Logistics in Iron and Steel Industry Using a Multi-objective Variable Neighborhood Search

机译:基于多目标变量邻域搜索的钢铁行业成品物流集成优化

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This paper is concerned with the integrated optimization of finished product logistics that consists of two sub-problems: consolidation planning and transportation scheduling. In this problem, three kinds of decisions should be made simultaneously, namely the selection of candidate finished products in each warehouse (i.e. , consolidation planning) and the vehicle allocation and transportation sequence of selected finished products in each warehouse (i.e. , transportation scheduling). Since the loading times of products to vehicles are sequence-dependent, a tradeoff should be made between two conflicting objectives: maximization of loadage of ships and maximization of efficiency of the whole logistics. In practical industry the schedulers usually handle the two sub-problems separately, which often cause much lower efficiency of the whole logistics and higher transportation cost. Therefore, in this paper the two sub-problems are integrated and formulated as a multi-objective mixed-integer programming model, and then a two-layer multi-objective variable neighborhood search (TLMOVNS) algorithm is developed to solve it. Computational results on simulated instances show that the proposed TLMOVNS is very efficient for this problem and much superior to the current scheduling method generally used in practice.
机译:本文关注的是成品物流的集成优化,它由两个子问题组成:合并计划和运输调度。在此问题中,应同时做出三种决策,即每个仓库中候选成品的选择(即合并计划)以及每个仓库中选定成品的车辆分配和运输顺序(即运输计划)。由于产品到车辆的装载时间取决于序列,因此应该在两个相互矛盾的目标之间进行权衡:最大的船舶装载量和最大的整体物流效率。在实际工业中,调度程序通常将两个子问题分开处理,这常常导致整个物流效率大大降低,运输成本更高。因此,本文将这两个子问题进行了整合并表述为一个多目标混合整数规划模型,然后开发了一种两层的多目标变量邻域搜索(TLMOVNS)算法来解决该问题。在模拟实例上的计算结果表明,所提出的TLMOVNS对于此问题非常有效,并且远远优于实际中通常使用的当前调度方法。

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