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

R. Tangkitjaroenmongkol, Supapom Kaittisin, S. Ongwattanakul
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引用次数: 5

Abstract

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.
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泰国入境物流木薯淀粉规划:基于GIS和K-means聚类方法的应用
应用地理信息系统(GIS)对物流进运系统中的木薯服务中心(CSC)位置进行分析,以收集木薯根的位置,并优化CSC的数量和位置适宜性。该方法采用k -均值聚类方法,结合空间和属性数据的地理信息系统,以及网络分析扩展,寻找、比较和最小化最优化的投资成本和交通距离解决方案。结果表明,CSC选址优化数量必须为20个节点,CSC选址投资成本减少到980万泰铢,距离为136,176.58公里,结果分别降低了49.5%和13.3%。
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