多列动车组高级修协同优化调度模型研究
首发时间:2019-12-02
摘要:近年来我国高速铁路建设取得了显著的成就,动车组保有量逾3000标准组,越来越多的动车组临近高级修周期,给既有的高级修检修基地带来了巨大的压力。如何合理安排动车组高级修基地的检修计划,提高检修吞吐量,提高关键设备利用率,对于提高高铁运营效率具有重要意义。本文针对目前高级修基地采用多列动车组并行检修模式,在动车组待检修配件BOM和检修工序拓扑图的双重约束下,以最小化关键设备的无效检修碎片时间、提高检修吞吐量为优化目标,构建优化模型。鉴于模型的非线性,采用先构建多列动车组协同高级修拓扑图,然后设计最大最小蚁群算法对模型进行优化求解,从而获得模型的最优或次优解。
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Research on the Cooperative Optimal Scheduling Model for Advanced Maintenance of Multiple EMUs
Abstract:In recent years, China's high-speed railway construction has made remarkable achievements. The number of EMUs is about to exceed 3000 standard units. Therefore, increasing number of EMUs is close to the advanced maintenance cycle, which brings great pressure to the existing advanced maintenance base. How to reasonably arrange the maintenance plan of EMU advanced maintenance base, arise the maintenance throughput, and improve the utilization rate of key equipment is of great significance to improve the operation efficiency of high-speed railway. In this paper, the parallel maintenance mode of multiple EMUs was adopted for the current advanced maintenance base. Under the dual-constraints of BOM of EMU parts to be overhauled and topology diagram of maintenance process, the optimization model was constructed to minimize the invalid maintenance debris time of key equipment and improve the maintenance throughput. In view of the non-linearity of the model, the topology map of multiple EMUs collaborative advanced repair was constructed first, based on which the maximum and minimum ant colony algorithm was designed to optimize the model, so as to obtain the optimal or sub optimal solution of the model.
Keywords: Emu Advanced Maintenance Transportation Organization Ant Colony Optimization Algorithm
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多列动车组高级修协同优化调度模型研究
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