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Multi-route planning of multimodal transportation for oversize and heavyweight cargo based on reconstruction

机译:基于重建的超大和重量级货物多式联运多式联运多途径规划

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This paper investigates the multi-route planning problem of multimodal transportation for oversize and heavyweight cargo based on reconstruction (MM-OHC-R). Considering required reconstruction of lines or nodes, a reconstruction model for route planning of OHC is proposed. The model aims to simultaneously determine the transportation route, modes of transport as well as the lines or nodes required to be reconstructed to minimize the total cost. To attain multiple solutions, the K shortest paths algorithm is introduced and improved to solve MM-OHC-R problem. The proposed algorithm is derived from a virtual network named multi-prism network and Yen algorithm. Moreover, the algorithm is improved by introducing improved A* algorithm. A case study is conducted to validate the feasibility of the proposed model and algorithms. The results demonstrate that the usage of reconstruction measurements is able to optimize the transportation schemes and the proposed algorithm is capable of developing multiple transportation schemes to provide the support of decision making and risk prevention and control for the carrier. For the constrained MM-OHC-R problem, the improvement of the A* algorithm enhances the computation performance by reducing the size of the candidate path set effectively.(c) 2020 Elsevier Ltd. All rights reserved.
机译:本文研究了基于重建(MM-OHC-R)的超大型和重量级货物多式联运多式联运多数型运输的多途径规划问题。考虑到所需的线条或节点的重建,提出了OCC路线规划的重建模型。该模型旨在同时确定运输路线,运输方式以及所需的线路或节点以最小化总成本。为了获得多种解决方案,介绍了K最短路径算法并改进以解决MM-OHC-R问题。所提出的算法源自名为多棱镜网络和日元算法的虚拟网络。此外,通过引入改进的A算法来提高该算法。进行案例研究以验证所提出的模型和算法的可行性。结果表明,重建测量的使用能够优化运输方案,所提出的算法能够开发多种运输方案,以提供对载体的决策和防止控制的支持。对于受约束的MM-OHC-R问题,A *算法的改进通过减少有效设置的候选路径的大小来增强计算性能。(c)2020 elestvier有限公司保留所有权利。

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