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Inbound logistics cassava starch planning: With application of GIS and K-means clustering methods in Thailand

机译:入境物流木薯淀粉计划:泰国GIS和K-MEARY集群方法的应用

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This paper present the decision support system in logistics inbound and transportation system with application of Geographic Information System (GIS) to analyse the Cassava Service Centres (CSC) location in order to collect cassava roots location and optimized the number and location suitability of CSC. The methodology used K-mean clustering and application of Geographic Information System with spatial and attribute data, and network analyst extension to find, compared and minimize optimization with cost for investment and transportation distance solution of their scenarios. The results had show the optimization number of location of CSC must be 20 nodes, investment cost for CSC location was reduced to 9.8 million baht, and distance was 136,176.58 kilometres, that results had reduce to 49.5 and 13.3 percent, respectively.
机译:本文介绍了物流入境和运输系统中的决策支持系统,应用地理信息系统(GIS)分析了木薯服务中心(CSC)位置,以收集木薯根位置并优化CSC的数量和位置适用性。该方法使用了k-mean群集和应用地理信息系统的空间和属性数据,以及网络分析员扩展,以查找,比较和最大限度地减少其场景的投资和运输距离解决方案的优化。结果显示了CSC的位置优化数量必须为20个节点,CSC地点的投资成本降至980万泰铢,距离为136,176.58公里,结果分别降至49.5和13.3%。

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