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Joint optimization of tow-trains dispatch and conflict-free route planning in mixed-model assembly lines

机译:混合模型装配线中的牵引培训派遣和无冲突路线规划的联合优化

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The increment of product variety and complex customer requirements has let many manufactures deliver flexible small-lot parts to mixed-model lines, causing a large consumption of energy. Tow-trains, consisting of an auto-guided vehicle (AGV) and several trailers carrying the bin filled with materials, have been widely employed in mixed-model assembly lines. This paper focuses on the joint optimization of the tow-trains dispatch and conflict-free route planning, aiming to minimize the sum of total energy consumption and delay. An integer programming model with extra conflict-free constraints is proposed for dispatching and routing problem (DRP). An approach integrated genetic algorithm and time-space graph-based ant colony algorithm is applied to jointly determine the optimal number of tow-trains and the sequence of tasks for each tow-train with a conflict-free route. Finally, a computational study is conducted to verify the performance of the proposed approach.
机译:产品品种和复杂客户要求的增量使许多制造商能够为混合模型线提供灵活的小批次,导致能量的大量消耗。 由自动引导的车辆(AGV)和带有材料填充物材料的夹具组成的牵引车已被广泛用于混合模型装配线。 本文重点介绍了牵引训练派遣和无冲突路线规划的联合优化,旨在最大限度地减少总能源消耗和延误的总和。 提出了一种包含额外不冲突约束的整数编程模型,用于调度和路由问题(DRP)。 一种方法集成遗传算法和基于时间空间图的蚁群算法应用于共同确定每种牵引列车的最佳牵引列车和任务序列,其中每个牵引列车都有不冲突路径。 最后,进行了计算研究以验证所提出的方法的性能。

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