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A New Prioritizing-Stacking Heuristic Algorithm for the Inner-City Truck Loading Problem

机译:一种解决城市卡车装载问题的新优先排序堆叠启发式算法

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Efficiently solving the truck loading problem (TLP) is crucial for achieving urban logistics objectives. Many heuristics, mainly based on wall-building and layer-building concepts, are presented in literature to solve this NP-hard problem. The current research presents a two-step novel prioritization-stacking heuristic algorithm for solving the TLP. The new algorithm primarily aims to improve the truck space utilization and reduce inventory costs at origin and destination points. In particular, the current work considers developing countries conditions in which demand is uncertain, cost minimization is prioritized over customer service, and routing optimization is complicated by a lot of traffic jams. The performance of the proposed heuristic is evaluated by applying it to a real-life case study from the Jordanian market. Additionally, the stacking part of the proposed heuristic is benchmarked with a literature data sample. Both implementations have proved the validity of the suggested heuristic algorithm.
机译:有效解决卡车装载问题(TLP)对于实现城市物流目标至关重要。文献中提出了许多主要基于墙构建和层构建概念的启发式方法来解决该NP难题。当前的研究提出了一种两步新颖的优先级排序-堆栈启发式算法来求解TLP。新算法的主要目的是提高卡车的空间利用率并减少起点和目的地的库存成本。特别是,当前的工作考虑了发展中国家的条件,在这些条件下需求是不确定的,成本最小化要优先于客户服务,并且由于许多交通拥堵而使路由优化变得复杂。通过将其应用于约旦市场上的实际案例研究,评估了所提出的启发式方法的性能。此外,所提出的启发式方法的堆栈部分以文献数据样本为基准。两种实现都证明了该启发式算法的有效性。

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