基于客户点多重特性的车辆路线优化

发布时间：2019-04-23 20:05

【摘要】：针对传统车辆路线优化研究在对客户点商品需求特性方面存在的不足,提出了先基于客户点多重特性进行聚类分析后进行线路优化的思想.首先,将语言变量值用梯形模糊数表示,对客户点和二级准则指标进行综合评价;其次,采用模糊集成方法将二级准则指标集成到一级准则指标上,将集成后的一级指标属性值拆分为4个分属性值参与聚类算法计算,并通过设计的聚类有效性指标选取合理的聚类结果;然后,应用模糊TOPSIS方法计算各类内的客户点优先级权重;最后,构建了客户点被选择服务的评价函数式,并与动态规划方法结合进行线路优化.文中还通过实例对所提方法的有效性进行了验证,并与现有方法进行了对比.结果表明,文中方法优于单纯以距离和客户点优先级权重为测度单位的方法,线路优化结果合理,并能应用到存在大规模客户点的车辆路线优化问题中.
[Abstract]:In view of the deficiency of traditional vehicle route optimization research in the demand characteristics of customer point commodity, the idea of cluster analysis based on customer point multiple characteristics and route optimization is put forward in this paper. Firstly, the value of language variable is expressed by trapezoidal fuzzy number, and the client point and second-level criterion index are evaluated synthetically. Secondly, the fuzzy integration method is used to integrate the two-level criterion index into the first-level criterion index, and the integrated first-order index attribute value is divided into four sub-attribute values to participate in the clustering algorithm calculation. And through the design of cluster validity index to select reasonable clustering results; Then, the fuzzy TOPSIS method is used to calculate the priority weights of client points. Finally, the evaluation function of the selected service of client points is constructed, and the line optimization is carried out in combination with the dynamic programming method. The validity of the proposed method is verified by an example and compared with the existing methods. The results show that the proposed method is superior to the method based on distance and priority weight of customer points. The route optimization results are reasonable and can be applied to vehicle routing optimization problems with large-scale customer points.
【作者单位】：东南大学交通学院;重庆交通大学管理学院;
【基金】：国家自然科学基金资助项目(51078087,51028802) 重庆市社会科学规划资助项目(2013YBJJ035)
【分类号】：U492.22

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