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An efficient heuristic for the multi-vehicle one-to-one pickup and delivery problem with split loads

机译:一种有效的启发式解决方案,用于多车一对一的分拣装载和运送问题

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摘要

In this study, we consider the Multi-vehicle One-to-one Pickup and Delivery Problem with Split Loads (MPDPSL). This problem is a generalization of the one-to-one Pickup and Delivery Problem (PDP) where each load can be served by multiple vehicles as well as multiple stops by the same vehicle. In practice, split deliveries is a viable option in many settings where the load can be physically split, such as courier services of third party logistics operators. We propose an efficient heuristic that combines the strengths of Tabu Search and Simulated Annealing for the solution of MPDPSL. Results from experiments on two problems sets in the literature indicate that the heuristic is capable of producing good quality solutions in reasonable time. The experiments also demonstrate that up to 33% savings can be obtained by allowing split loads; however, the magnitude of savings is dependent largely on the spatial distribution of the pickup and delivery points.
机译:在这项研究中,我们考虑了多车一对一的分担货运接送问题(MPDPSL)。这个问题是一对一的提货和运送问题(PDP)的概括,其中每个负载可以由多辆车提供服务,也可以由同一辆车提供多个停靠点。实际上,在许多可以物理拆分负载的环境中,例如第三方物流运营商的快递服务,拆分交付是一个可行的选择。我们提出一种有效的启发式方法,结合禁忌搜索和模拟退火的优势来解决MPDPSL。文献中针对两个问题集的实验结果表明,启发式算法能够在合理的时间内产生高质量的解决方案。实验还表明,允许分担载荷最多可节省33%的费用。但是,节省的幅度在很大程度上取决于取货点和交货点的空间分布。

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