为快速、高效地完成烟草配送过程,在兼顾地区特点的情况下减少配送成本和时间,以人工智能、运筹学等方法为理论依据,结合聚类分析算法对广西烟草物流配送过程进行了优化设计。基于聚类分析给出了优化算法模型及步骤,对烟草物流配送线路进行了中转站的区域规划、周期配送区域(片区时间区域)规划和线路优化。应用效果表明,优化后中转站数量由10个减少为7个,总配送路线减少30%,配送节点更集中,节省了配送费用和时间,提高了烟草物流的运营效率。
In order to quickly and efficiently deliver tobacco products and reduce the cost and time of delivery, according to its regional characters, the tobacco product delivery process of Guangxi was optimized by taking artificial intelligence, operations research and other methods as theoretical bases combining with cluster analysis algorithm. The optimization algorithm model and procedures were proposed based on cluster analysis, and the regional plannings for transit stations and periodic delivery areas were conducted and the delivery routes for the later were optimized. The results of application showed that, after optimization, the number of transit stations reduced from 10 to 7 and delivery routes decreased by 30% in total. Delivery nodes became more concentrated, the cost and time of delivery were saved, and the operational efficiency of tobacco logistics was improved.