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基于两阶段法的多车型卷烟配送路径优化研究 被引量:1

Research on Distribution Route Optimization of Multi-model Cigarette Based on Two-stage Method
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摘要 在烟草商业企业中,物流是其重要的环节,是连接客户与烟草企业间的纽带,其卷烟配送线路设计的合理与否直接影响到卷烟的配送效率和配送成本,就如何合理的规划线路成为卷烟配送的关键问题。文章以Q烟草公司为例,运用先分组后路线的两阶段法对问题进行求解,先利用K-means聚类算法对区域进行划分,再考虑工作量均衡的条件下引入遗传算法对区域进一步调整,最后利用混合遗传算法对各配送区域进行线路优化,通过实例从线路数、车辆数、空载率、配送里程及总成本等指标上可以看出两阶段法的配送效果更优。 In the tobacco commercial enterprise,logistics is the important link,is the connection between the customer and tobacco enterprise bond,the cigarette distribution circuit design is reasonable or not directly affect the efficiency of cigarette distribution and distribution costs,how to reasonable planning becomes the key issue in the cigarette distribution.Based on Q tobacco company as an example,this paper USES group before the two-stage method to solve the problem of the route,the first use of K-means clustering algorithm for regional division,using the hybrid genetic algorithm for the route optimization distribution area,by examples from the line number,the number of vehicles,the empty loading rate,distribution range and the total cost on indicators such as you can see two stage method of distribution effect is better and embedded mountain climbing algorithm.
作者 赵峰 王泽 李轶 ZHAO Feng;WANG Ze;LI Yi(Anhui University of Technology,Maanshan 243032,China;Maanshan Tobacco Monopoly Bureau,Maanshan 243032,China)
出处 《物流科技》 2020年第1期30-34,44,共6页 Logistics Sci-Tech
基金 国家自然科学基金项目(71872002) 安徽省高校人文社会科学研究重点项目(SK2019A0072)
关键词 路线优化 多车型 K-MEANS聚类算法 混合遗传算法 route optimization multi-vehicle K-means clustering algorithm hybrid genetic algorithm
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