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首页> 外文期刊>Journal of advances in management research >Distribution planning using capacitated clustering and vehicle routing problem A case of Indian cooperative dairy
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Distribution planning using capacitated clustering and vehicle routing problem A case of Indian cooperative dairy

机译：基于能力集群和车辆路径问题的分销计划-以印度合作乳业为例

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摘要

Purpose - The purpose of this paper is to reduce the distribution cost of an Indian cooperative dairy. The reduction of cost was achieved with the application of the clustering method (k-means clustering) and capacitated vehicle routing problem (cheapest link algorithm (CLA)). Design/methodology/approach - Capacitated k-means clustering was used to split delivery locations into similar size groups (i.e. clusters) based on proximity without exceeding a specified total cluster capacity. Each cluster would be served by a local stockist. CLA was then used to find delivery routes from dairy (i.e. depot) to stockist in each cluster and from stockist to all other delivery locations within the cluster. Findings - K-means clustering and CLA suggested optimal delivery routes on which vehicles will run. The complete algorithm was able to provide a solution within 30 s. Practical implications - Clustering of delivery locations and use of heterogeneous fleet of delivery vehicles can result in considerable savings in daily operational cost. Originality/value - Most of the research related to the use of demand clustering to improve distribution routes has been theoretical, which do not take into account real-world limitations like vehicle's specific limitations. The authors tried to address that gap by taking a real-world case of a cooperative dairy and compared the result with existing distribution routes used by dairy. This work can be used by other dairies or distribution companies according to their scenario.
机译：目的-本文的目的是降低印度合作乳业的分销成本。通过使用聚类方法（k均值聚类）和车辆容量受限的问题（最便宜的链接算法（CLA）），降低了成本。设计/方法/方法-容量k均值聚类用于根据接近程度将传递位置分为相似大小的组（即聚类），而不会超过指定的总聚类容量。每个群集将由本地库存商提供服务。然后使用CLA查找从乳制品（即仓库）到每个集群中的库存商以及从零售商到集群中所有其他交付地点的交付路线。调查结果-K-means聚类分析和CLA建议了车辆可行驶的最佳运输路线。完整的算法能够在30秒内提供解决方案。实际意义-集中运输地点并使用不同种类的运输车辆可以节省大量日常运营成本。原创性/价值-与使用需求集群来改善分销路线有关的大多数研究都是理论上的，没有考虑到现实世界中的限制，例如车辆的特定限制。作者试图通过在合作乳业的实际案例中解决这一差距，并将结果与​​乳业使用的现有分销途径进行比较。其他乳品厂或经销公司可以根据自己的情况使用这项工作。

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