基于整数规划的汽车零部件仓库拣货路径优化

Janyaporn Cheewapongpan, A. Butrat, S. Supsomboon
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引用次数: 0

摘要

许多工厂都面临着运输耗时的问题。在汽车装配线上,装配一辆汽车要挑选一万多个零件。拣货是在仓库中运输和收集物品以服务内部和外部客户的过程。因此,这通常被认为是仓库活动中消耗最多的时间,特别是在旅行活动中。旅行商问题(TSP)是一种求解最短路径的问题。本文建立了TSP的数学模型,使拣货机的行走距离最小,并给出了最优拣货顺序。采用二进制整数规划(BIP)对模型进行求解。MIP库被用作在Python中操作的问题解决器。案例研究证明了所提出模型的解决方案质量。结果表明,通过减少行走距离对拣货路线进行了优化。
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Optimal Order Picking Route in Automotive Part Warehouse using Integer Programming
Many factories are facing the problem of transportation time consumption. In the car assembly line, there are more than ten thousand parts to pick for assembling a single car. Order picking is the process which transport and collect the items in the warehouse to serve both internal and external customer. Consequently, this is generally known as the most consumed time in warehouse activities, especially in the traveling activity. Traveling Salesman Problem (TSP) is the technique which deals with finding the shortest route. This paper presents a mathematical model of TSP to minimize the traveled distance of pickers and provide the optimal sequence of order picking. Binary integer programming (BIP) is applied to solve the model. The MIP library is used as the problem solver which operates in Python. The case studies are introduced to demonstrate the solution quality of the proposed model. The result shows that order picking route is optimized by decreasing the distance traveled.
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